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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2101.10964 | Oren Neumann | Oren Neumann, Claudius Gros | Investment vs. reward in a competitive knapsack problem | null | Learning Meets Combinatorial Algorithms at NeurIPS2020 (2020) | null | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Natural selection drives species to develop brains, with sizes that increase
with the complexity of the tasks to be tackled. Our goal is to investigate the
balance between the metabolic costs of larger brains compared to the advantage
they provide in solving general and combinatorial problems. Defining advantage
as t... | [
{
"created": "Tue, 26 Jan 2021 17:47:56 GMT",
"version": "v1"
}
] | 2021-01-28 | [
[
"Neumann",
"Oren",
""
],
[
"Gros",
"Claudius",
""
]
] |
2101.10977 | Lukas Brunke | Lukas Brunke, Prateek Agrawal, Nikhil George | Evaluating Input Perturbation Methods for Interpreting CNNs and Saliency
Map Comparison | null | ECCV 2020: Computer Vision - ECCV 2020 Workshops pp 120-134 | 10.1007/978-3-030-66415-2_8 | null | cs.LG cs.CV | http://creativecommons.org/licenses/by/4.0/ | Input perturbation methods occlude parts of an input to a function and
measure the change in the function's output. Recently, input perturbation
methods have been applied to generate and evaluate saliency maps from
convolutional neural networks. In practice, neutral baseline images are used
for the occlusion, such th... | [
{
"created": "Tue, 26 Jan 2021 18:11:06 GMT",
"version": "v1"
}
] | 2021-01-27 | [
[
"Brunke",
"Lukas",
""
],
[
"Agrawal",
"Prateek",
""
],
[
"George",
"Nikhil",
""
]
] |
2101.11002 | Evan Debenham | Evan R.M. Debenham and Roberto Solis-Oba (The University of Western
Ontario, Canada) | New Algorithms for Computing Field of Vision over 2D Grids | Presented at the 6th International Conference on Computer Science,
Engineering And Applications (CSEA 2020) 18 pages, 11 figures, 4 tables | 6th International Conference on Computer Science, Engineering And
Applications (CSEA 2020), Volume 10, Number 18, December 2020, pg. 1-18 | null | null | cs.CV | http://creativecommons.org/licenses/by-sa/4.0/ | The aim of this paper is to propose new algorithms for Field of Vision (FOV)
computation which improve on existing work at high resolutions. FOV refers to
the set of locations that are visible from a specific position in a scene of a
computer game.
We summarize existing algorithms for FOV computation, describe thei... | [
{
"created": "Tue, 26 Jan 2021 20:38:35 GMT",
"version": "v1"
}
] | 2021-01-28 | [
[
"Debenham",
"Evan R. M.",
"",
"The University of Western\n Ontario, Canada"
],
[
"Solis-Oba",
"Roberto",
"",
"The University of Western\n Ontario, Canada"
]
] |
2101.11023 | Taro Sakurai | Taro Sakurai (Chiba University) | On formal concepts of random formal contexts | 7 pages, 2 figures, 1 table | Information Sciences 578 (2021) 615-620 | 10.1016/j.ins.2021.07.065 | null | cs.AI cs.DS math.CO | http://creativecommons.org/licenses/by/4.0/ | In formal concept analysis, it is well-known that the number of formal
concepts can be exponential in the worst case. To analyze the average case, we
introduce a probabilistic model for random formal contexts and prove that the
average number of formal concepts has a superpolynomial asymptotic lower bound.
| [
{
"created": "Tue, 26 Jan 2021 19:00:06 GMT",
"version": "v1"
}
] | 2021-08-02 | [
[
"Sakurai",
"Taro",
"",
"Chiba University"
]
] |
2101.11060 | Xinwei Zhao | Xinwei Zhao and Matthew C. Stamm | Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers | null | This paper is published on European Conference on Computer Vision
2020, page 202-219, Springer | null | null | cs.CR cs.CV | http://creativecommons.org/licenses/by/4.0/ | Recently, physical domain adversarial attacks have drawn significant
attention from the machine learning community. One important attack proposed by
Eykholt et al. can fool a classifier by placing black and white stickers on an
object such as a road sign. While this attack may pose a significant threat to
visual clas... | [
{
"created": "Tue, 26 Jan 2021 19:59:28 GMT",
"version": "v1"
}
] | 2021-01-28 | [
[
"Zhao",
"Xinwei",
""
],
[
"Stamm",
"Matthew C.",
""
]
] |
2101.11081 | Xinwei Zhao | Xinwei Zhao and Matthew C. Stamm | The Effect of Class Definitions on the Transferability of Adversarial
Attacks Against Forensic CNNs | null | Published at Electronic Imaging, Media Watermarking, Security, and
Forensics 2020, pp. 119-1-119-7(7) | null | null | cs.CV cs.CR cs.LG | http://creativecommons.org/licenses/by/4.0/ | In recent years, convolutional neural networks (CNNs) have been widely used
by researchers to perform forensic tasks such as image tampering detection. At
the same time, adversarial attacks have been developed that are capable of
fooling CNN-based classifiers. Understanding the transferability of adversarial
attacks,... | [
{
"created": "Tue, 26 Jan 2021 20:59:37 GMT",
"version": "v1"
}
] | 2021-01-28 | [
[
"Zhao",
"Xinwei",
""
],
[
"Stamm",
"Matthew C.",
""
]
] |
2101.11174 | Weiwei Jiang | Weiwei Jiang, Jiayun Luo | Graph Neural Network for Traffic Forecasting: A Survey | null | Expert Systems with Applications Volume, vol. 207, 30 November
2022, 117921 | 10.1016/j.eswa.2022.117921 | null | cs.LG cs.AI | http://creativecommons.org/licenses/by/4.0/ | Traffic forecasting is important for the success of intelligent
transportation systems. Deep learning models, including convolution neural
networks and recurrent neural networks, have been extensively applied in
traffic forecasting problems to model spatial and temporal dependencies. In
recent years, to model the gra... | [
{
"created": "Wed, 27 Jan 2021 02:35:41 GMT",
"version": "v1"
},
{
"created": "Mon, 15 Feb 2021 14:19:27 GMT",
"version": "v2"
},
{
"created": "Tue, 30 Nov 2021 16:27:26 GMT",
"version": "v3"
},
{
"created": "Tue, 22 Feb 2022 05:46:58 GMT",
"version": "v4"
}
] | 2022-07-08 | [
[
"Jiang",
"Weiwei",
""
],
[
"Luo",
"Jiayun",
""
]
] |
2101.11183 | Haipeng Li | Haipeng Li, Shuaicheng Liu, Jue Wang | DeepOIS: Gyroscope-Guided Deep Optical Image Stabilizer Compensation | null | IEEE Transactions on Circuits and Systems for Video Technology (
Volume: 32, Issue: 5, May 2022) | 10.1109/TCSVT.2021.3103281 | 21690602 | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mobile captured images can be aligned using their gyroscope sensors. Optical
image stabilizer (OIS) terminates this possibility by adjusting the images
during the capturing. In this work, we propose a deep network that compensates
the motions caused by the OIS, such that the gyroscopes can be used for image
alignment... | [
{
"created": "Wed, 27 Jan 2021 03:23:46 GMT",
"version": "v1"
},
{
"created": "Tue, 4 Jul 2023 07:30:21 GMT",
"version": "v2"
}
] | 2023-07-06 | [
[
"Li",
"Haipeng",
""
],
[
"Liu",
"Shuaicheng",
""
],
[
"Wang",
"Jue",
""
]
] |
2101.11217 | Tejas Khare | Tejas Atul Khare and Anuradha C. Phadke | Automated Crop Field Surveillance using Computer Vision | 6 Pages, 10 Figures | Proceedings reference - 978-1-7281-9885-9/20/$31.00
\c{opyright}2020 IEEE | 10.1109/DISCOVER50404.2020.9278072 | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Artificial Intelligence is everywhere today. But unfortunately, Agriculture
has not been able to get that much attention from Artificial Intelligence (AI).
A lack of automation persists in the agriculture industry. For over many years,
farmers and crop field owners have been facing a problem of trespassing of wild
an... | [
{
"created": "Wed, 27 Jan 2021 05:58:28 GMT",
"version": "v1"
}
] | 2021-01-28 | [
[
"Khare",
"Tejas Atul",
""
],
[
"Phadke",
"Anuradha C.",
""
]
] |
2101.11302 | Niels van der Heijden | Niels van der Heijden, Helen Yannakoudakis, Pushkar Mishra, Ekaterina
Shutova | Multilingual and cross-lingual document classification: A meta-learning
approach | 11 pages, 1 figure | Association for Computational Linguistics, Proceedings of the 16th
Conference of the European Chapter of the Association for Computational
Linguistics: Main Volume, 2021, 1966--1976 | null | null | cs.CL | http://creativecommons.org/licenses/by/4.0/ | The great majority of languages in the world are considered under-resourced
for the successful application of deep learning methods. In this work, we
propose a meta-learning approach to document classification in limited-resource
setting and demonstrate its effectiveness in two different settings: few-shot,
cross-lin... | [
{
"created": "Wed, 27 Jan 2021 10:22:56 GMT",
"version": "v1"
},
{
"created": "Sat, 24 Apr 2021 10:24:38 GMT",
"version": "v2"
}
] | 2021-04-27 | [
[
"van der Heijden",
"Niels",
""
],
[
"Yannakoudakis",
"Helen",
""
],
[
"Mishra",
"Pushkar",
""
],
[
"Shutova",
"Ekaterina",
""
]
] |
2101.11431 | Nicola Melluso | Silvia Fareri, Nicola Melluso, Filippo Chiarello, Gualtiero Fantoni | SkillNER: Mining and Mapping Soft Skills from any Text | null | Expert Systems With Applications 184 (2021) 115544 | 10.1016/j.eswa.2021.115544 | null | cs.CL cs.IR | http://creativecommons.org/licenses/by/4.0/ | In today's digital world, there is an increasing focus on soft skills. On the
one hand, they facilitate innovation at companies, but on the other, they are
unlikely to be automated soon. Researchers struggle with accurately approaching
quantitatively the study of soft skills due to the lack of data-driven methods
to ... | [
{
"created": "Fri, 22 Jan 2021 11:14:05 GMT",
"version": "v1"
},
{
"created": "Mon, 12 Jul 2021 18:12:46 GMT",
"version": "v2"
}
] | 2021-07-14 | [
[
"Fareri",
"Silvia",
""
],
[
"Melluso",
"Nicola",
""
],
[
"Chiarello",
"Filippo",
""
],
[
"Fantoni",
"Gualtiero",
""
]
] |
2101.11435 | Yakup Kutlu | Apdullah Yayik, Yakup Kutlu | Online LDA based brain-computer interface system to aid disabled people | 13 pages, 4 figures, Natural and Engineering Sciences | Natural and Engineering Sciences, 2017 | null | null | cs.HC cs.AI | http://creativecommons.org/licenses/by/4.0/ | This paper aims to develop brain-computer interface system based on
electroencephalography that can aid disabled people in daily life. The system
relies on one of the most effective event-related potential wave, P300, which
can be elicited by oddball paradigm. Developed application has a basic
interaction tool that e... | [
{
"created": "Thu, 21 Jan 2021 08:17:05 GMT",
"version": "v1"
}
] | 2021-01-28 | [
[
"Yayik",
"Apdullah",
""
],
[
"Kutlu",
"Yakup",
""
]
] |
2101.11436 | Yakup Kutlu | Kadir Tohma, Yakup Kutlu | Challenges Encountered in Turkish Natural Language Processing Studies | 8 pages, Natural and Engineering Sciences | Natural and Engineering Sciences, 2020 | null | null | cs.CL cs.AI | http://creativecommons.org/licenses/by/4.0/ | Natural language processing is a branch of computer science that combines
artificial intelligence with linguistics. It aims to analyze a language element
such as writing or speaking with software and convert it into information.
Considering that each language has its own grammatical rules and vocabulary
diversity, th... | [
{
"created": "Thu, 21 Jan 2021 08:30:33 GMT",
"version": "v1"
}
] | 2021-01-28 | [
[
"Tohma",
"Kadir",
""
],
[
"Kutlu",
"Yakup",
""
]
] |
2101.11508 | Olivier Rukundo | Olivier Rukundo | Effects of Image Size on Deep Learning | 22 pages, 23 figures, 5 tables | Electronics 2023, 12(4), 985 | 10.3390/electronics12040985 | null | cs.CV cs.LG eess.IV | http://creativecommons.org/licenses/by/4.0/ | In this work, the best size for late gadolinium enhancement (LGE) magnetic
resonance imaging (MRI) images in the training dataset was determined to
optimize deep learning training outcomes. Non-extra pixel and extra pixel
interpolation algorithms were used to determine the new size of the LGE-MRI
images. A novel stra... | [
{
"created": "Wed, 27 Jan 2021 16:07:48 GMT",
"version": "v1"
},
{
"created": "Mon, 26 Jul 2021 20:25:11 GMT",
"version": "v2"
},
{
"created": "Mon, 23 May 2022 20:16:05 GMT",
"version": "v3"
},
{
"created": "Thu, 28 Jul 2022 19:12:58 GMT",
"version": "v4"
},
{
"c... | 2023-02-20 | [
[
"Rukundo",
"Olivier",
""
]
] |
2101.11560 | Ece Calikus | Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, and Onur
Dikmen | Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly
Detection | null | Data Mining Knowledge Discovery (2022) | 10.1007/s10618-022-00868-7 | null | cs.LG cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In contextual anomaly detection, an object is only considered anomalous
within a specific context. Most existing methods for CAD use a single context
based on a set of user-specified contextual features. However, identifying the
right context can be very challenging in practice, especially in datasets, with
a large n... | [
{
"created": "Wed, 27 Jan 2021 17:34:13 GMT",
"version": "v1"
},
{
"created": "Thu, 15 Apr 2021 23:16:56 GMT",
"version": "v2"
},
{
"created": "Mon, 24 Jan 2022 17:34:32 GMT",
"version": "v3"
},
{
"created": "Tue, 4 Oct 2022 12:50:05 GMT",
"version": "v4"
}
] | 2022-10-05 | [
[
"Calikus",
"Ece",
""
],
[
"Nowaczyk",
"Slawomir",
""
],
[
"Bouguelia",
"Mohamed-Rafik",
""
],
[
"Dikmen",
"Onur",
""
]
] |
2101.11587 | Steven Frank | Steven J. Frank | The Work of Art in an Age of Mechanical Generation | This is the author's final version; the article has been accepted for
publication in Leonardo Journal | Leonardo(2022) 55(4): 378-381 | 10.1162/leon_a_02095 | null | cs.CY cs.AI cs.CV | http://creativecommons.org/licenses/by/4.0/ | Can we define what it means to be "creative," and if so, can our definition
drive artificial intelligence (AI) systems to feats of creativity
indistinguishable from human efforts? This mixed question is considered from
technological and social perspectives. Beginning with an exploration of the
value we attach to auth... | [
{
"created": "Wed, 27 Jan 2021 18:32:58 GMT",
"version": "v1"
},
{
"created": "Wed, 10 Aug 2022 19:31:02 GMT",
"version": "v2"
}
] | 2022-08-12 | [
[
"Frank",
"Steven J.",
""
]
] |
2101.11717 | Francois Malgouyres | Adrien Gauffriau, Fran\c{c}ois Malgouyres (IMT), M\'elanie Ducoffe | Overestimation learning with guarantees | null | AAAI-21, workshop on safeAI, Feb 2021, Valence (Virtual), Spain | null | null | cs.LG cs.AI cs.NE stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We describe a complete method that learns a neural network which is
guaranteed to overestimate a reference function on a given domain. The neural
network can then be used as a surrogate for the reference function. The method
involves two steps. In the first step, we construct an adaptive set of Majoring
Points. In th... | [
{
"created": "Tue, 26 Jan 2021 09:06:03 GMT",
"version": "v1"
}
] | 2021-01-29 | [
[
"Gauffriau",
"Adrien",
"",
"IMT"
],
[
"Malgouyres",
"François",
"",
"IMT"
],
[
"Ducoffe",
"Mélanie",
""
]
] |
2101.11844 | Iena Petronella Derks | Iena Petronella Derks and Alta de Waal | A Taxonomy of Explainable Bayesian Networks | null | In: Gerber A. (eds) Artificial Intelligence Research. SACAIR 2021.
Communications in Computer and Information Science, vol 1342. Springer, Cham
(2020) | 10.1007/978-3-030-66151-9_14 | null | cs.AI | http://creativecommons.org/licenses/by/4.0/ | Artificial Intelligence (AI), and in particular, the explainability thereof,
has gained phenomenal attention over the last few years. Whilst we usually do
not question the decision-making process of these systems in situations where
only the outcome is of interest, we do however pay close attention when these
systems... | [
{
"created": "Thu, 28 Jan 2021 07:29:57 GMT",
"version": "v1"
}
] | 2021-01-29 | [
[
"Derks",
"Iena Petronella",
""
],
[
"de Waal",
"Alta",
""
]
] |
2101.11978 | Rodrigo Agerri | Elena Zotova, Rodrigo Agerri, German Rigau | Semi-automatic Generation of Multilingual Datasets for Stance Detection
in Twitter | Stance detection, multilingualism, text categorization, fake news,
deep learning | Expert Systems with Applications, 170 (2021), Elsevier | 10.1016/j.eswa.2020.114547 | null | cs.CL | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Popular social media networks provide the perfect environment to study the
opinions and attitudes expressed by users. While interactions in social media
such as Twitter occur in many natural languages, research on stance detection
(the position or attitude expressed with respect to a specific topic) within
the Natura... | [
{
"created": "Thu, 28 Jan 2021 13:05:09 GMT",
"version": "v1"
}
] | 2021-01-29 | [
[
"Zotova",
"Elena",
""
],
[
"Agerri",
"Rodrigo",
""
],
[
"Rigau",
"German",
""
]
] |
2101.12047 | Samuel Alexander | Samuel Alexander, Bill Hibbard | Measuring Intelligence and Growth Rate: Variations on Hibbard's
Intelligence Measure | 25 pages | Journal of Artificial General Intelligence 12(1), 2021 | 10.2478/jagi-2021-0001 | null | cs.AI | http://creativecommons.org/licenses/by-nc-nd/4.0/ | In 2011, Hibbard suggested an intelligence measure for agents who compete in
an adversarial sequence prediction game. We argue that Hibbard's idea should
actually be considered as two separate ideas: first, that the intelligence of
such agents can be measured based on the growth rates of the runtimes of the
competito... | [
{
"created": "Mon, 25 Jan 2021 01:54:08 GMT",
"version": "v1"
}
] | 2021-01-29 | [
[
"Alexander",
"Samuel",
""
],
[
"Hibbard",
"Bill",
""
]
] |
2101.12072 | Kashif Rasul | Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf | Autoregressive Denoising Diffusion Models for Multivariate Probabilistic
Time Series Forecasting | null | Proceedings of the 38th International Conference on Machine
Learning, PMLR 139:8857-8868, 2021 | null | null | cs.LG cs.AI | http://creativecommons.org/licenses/by/4.0/ | In this work, we propose \texttt{TimeGrad}, an autoregressive model for
multivariate probabilistic time series forecasting which samples from the data
distribution at each time step by estimating its gradient. To this end, we use
diffusion probabilistic models, a class of latent variable models closely
connected to s... | [
{
"created": "Thu, 28 Jan 2021 15:46:10 GMT",
"version": "v1"
},
{
"created": "Tue, 2 Feb 2021 12:32:30 GMT",
"version": "v2"
}
] | 2021-07-09 | [
[
"Rasul",
"Kashif",
""
],
[
"Seward",
"Calvin",
""
],
[
"Schuster",
"Ingmar",
""
],
[
"Vollgraf",
"Roland",
""
]
] |
2101.12102 | Samuel Rivera | Deborah Weeks and Samuel Rivera | Domain Adaptation by Topology Regularization | null | SPIE Defense + Commercial Sensing, 2021 | null | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Deep learning has become the leading approach to assisted target recognition.
While these methods typically require large amounts of labeled training data,
domain adaptation (DA) or transfer learning (TL) enables these algorithms to
transfer knowledge from a labelled (source) data set to an unlabelled but
related (ta... | [
{
"created": "Thu, 28 Jan 2021 16:45:41 GMT",
"version": "v1"
}
] | 2021-01-29 | [
[
"Weeks",
"Deborah",
""
],
[
"Rivera",
"Samuel",
""
]
] |
2101.12136 | Ghada Sokar | Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy | Self-Attention Meta-Learner for Continual Learning | null | 20th International Conference on Autonomous Agents and Multiagent
Systems (AAMAS 2021) | null | null | cs.LG cs.AI cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Continual learning aims to provide intelligent agents capable of learning
multiple tasks sequentially with neural networks. One of its main challenging,
catastrophic forgetting, is caused by the neural networks non-optimal ability
to learn in non-stationary distributions. In most settings of the current
approaches, t... | [
{
"created": "Thu, 28 Jan 2021 17:35:04 GMT",
"version": "v1"
}
] | 2021-01-29 | [
[
"Sokar",
"Ghada",
""
],
[
"Mocanu",
"Decebal Constantin",
""
],
[
"Pechenizkiy",
"Mykola",
""
]
] |
2101.12446 | Matthew Olson | Matthew L. Olson, Roli Khanna, Lawrence Neal, Fuxin Li, Weng-Keen Wong | Counterfactual State Explanations for Reinforcement Learning Agents via
Generative Deep Learning | Full source code available at
https://github.com/mattolson93/counterfactual-state-explanations | Artificial Intelligence, 2021, 103455, ISSN 0004-3702 | 10.1016/j.artint.2021.103455 | null | cs.AI cs.HC cs.LG | http://creativecommons.org/licenses/by/4.0/ | Counterfactual explanations, which deal with "why not?" scenarios, can
provide insightful explanations to an AI agent's behavior. In this work, we
focus on generating counterfactual explanations for deep reinforcement learning
(RL) agents which operate in visual input environments like Atari. We introduce
counterfact... | [
{
"created": "Fri, 29 Jan 2021 07:43:41 GMT",
"version": "v1"
}
] | 2021-02-01 | [
[
"Olson",
"Matthew L.",
""
],
[
"Khanna",
"Roli",
""
],
[
"Neal",
"Lawrence",
""
],
[
"Li",
"Fuxin",
""
],
[
"Wong",
"Weng-Keen",
""
]
] |
2101.12463 | Hao Li | Chenghao Chen and Hao Li | Robust Representation Learning with Feedback for Single Image Deraining | null | IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR),
2021, pp.7742-7751 | null | null | eess.IV cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A deraining network can be interpreted as a conditional generator that aims
at removing rain streaks from image. Most existing image deraining methods
ignore model errors caused by uncertainty that reduces embedding quality.
Unlike existing image deraining methods that embed low-quality features into
the model direct... | [
{
"created": "Fri, 29 Jan 2021 08:20:50 GMT",
"version": "v1"
},
{
"created": "Wed, 3 Feb 2021 05:58:20 GMT",
"version": "v2"
},
{
"created": "Sun, 20 Jun 2021 09:42:53 GMT",
"version": "v3"
}
] | 2021-06-22 | [
[
"Chen",
"Chenghao",
""
],
[
"Li",
"Hao",
""
]
] |
2102.00322 | Vaneet Aggarwal | Mayank Gupta and Lingjun Chen and Denny Yu and Vaneet Aggarwal | A Supervised Learning Approach for Robust Health Monitoring using Face
Videos | The main part of the paper appeared in DFHS'20: Proceedings of the
2nd ACM Workshop on Device-Free Human Sensing; while the Supplementary did
not appear in the proceedings | Proceedings of the 2nd ACM Workshop on Device-Free Human Sensing
(DFHS 2020) Nov. 2020 pp. 6-10 | 10.1145/3427772.3429392 | null | cs.CV cs.HC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Monitoring of cardiovascular activity is highly desired and can enable novel
applications in diagnosing potential cardiovascular diseases and maintaining an
individual's well-being. Currently, such vital signs are measured using
intrusive contact devices such as an electrocardiogram (ECG), chest straps, and
pulse oxi... | [
{
"created": "Sat, 30 Jan 2021 22:03:16 GMT",
"version": "v1"
}
] | 2021-02-02 | [
[
"Gupta",
"Mayank",
""
],
[
"Chen",
"Lingjun",
""
],
[
"Yu",
"Denny",
""
],
[
"Aggarwal",
"Vaneet",
""
]
] |
2102.00385 | Guangsheng Bao | Guangsheng Bao and Yue Zhang | Contextualized Rewriting for Text Summarization | null | AAAI 2021 | null | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Extractive summarization suffers from irrelevance, redundancy and
incoherence. Existing work shows that abstractive rewriting for extractive
summaries can improve the conciseness and readability. These rewriting systems
consider extracted summaries as the only input, which is relatively focused but
can lose important... | [
{
"created": "Sun, 31 Jan 2021 05:35:57 GMT",
"version": "v1"
},
{
"created": "Mon, 26 Apr 2021 06:29:16 GMT",
"version": "v2"
}
] | 2021-04-27 | [
[
"Bao",
"Guangsheng",
""
],
[
"Zhang",
"Yue",
""
]
] |
2102.00515 | Fatih Uysal | Fatih Uysal, F{\i}rat Hardala\c{c}, Ozan Peker, Tolga Tolunay and Nil
Tokg\"oz | Classification of Shoulder X-Ray Images with Deep Learning Ensemble
Models | This paper is accepted at Applied Sciences, MDPI, 2021, 11(6), 2723.
Section: "Applied Biosciences and Bioengineering". Special Issue: "Advancing
Biomedical Image Retrieval and Classification for Computer Aided Diagnosis" | Applied Sciences, MDPI, 2021, 11(6), 2723. Section: "Applied
Biosciences and Bioengineering". Special Issue: "Advancing Biomedical Image
Retrieval and Classification for Computer Aided Diagnosis" | 10.3390/app11062723 | null | eess.IV cs.CV cs.LG | http://creativecommons.org/licenses/by/4.0/ | Fractures occur in the shoulder area, which has a wider range of motion than
other joints in the body, for various reasons. To diagnose these fractures,
data gathered from Xradiation (X-ray), magnetic resonance imaging (MRI), or
computed tomography (CT) are used. This study aims to help physicians by
classifying shou... | [
{
"created": "Sun, 31 Jan 2021 19:20:04 GMT",
"version": "v1"
},
{
"created": "Mon, 1 Mar 2021 12:09:24 GMT",
"version": "v2"
},
{
"created": "Sat, 20 Mar 2021 18:28:30 GMT",
"version": "v3"
}
] | 2021-03-23 | [
[
"Uysal",
"Fatih",
""
],
[
"Hardalaç",
"Fırat",
""
],
[
"Peker",
"Ozan",
""
],
[
"Tolunay",
"Tolga",
""
],
[
"Tokgöz",
"Nil",
""
]
] |
2102.00760 | Vivien Cabannes | Vivien Cabannes and Alessandro Rudi and Francis Bach | Fast rates in structured prediction | 14 main pages, 3 main figures, 43 pages, 4 figures (with appendix) | Conference on Learning Theory, PMLR 134, 2021 | null | null | stat.ML cs.AI cs.LG math.ST stat.TH | http://creativecommons.org/licenses/by/4.0/ | Discrete supervised learning problems such as classification are often
tackled by introducing a continuous surrogate problem akin to regression.
Bounding the original error, between estimate and solution, by the surrogate
error endows discrete problems with convergence rates already shown for
continuous instances. Ye... | [
{
"created": "Mon, 1 Feb 2021 10:50:04 GMT",
"version": "v1"
},
{
"created": "Tue, 8 Jun 2021 13:02:31 GMT",
"version": "v2"
},
{
"created": "Thu, 15 Jul 2021 15:04:41 GMT",
"version": "v3"
}
] | 2021-07-16 | [
[
"Cabannes",
"Vivien",
""
],
[
"Rudi",
"Alessandro",
""
],
[
"Bach",
"Francis",
""
]
] |
2102.00838 | Rafael Angarita | Shufan Jiang (CRESTIC, ISEP), Rafael Angarita (ISEP), Stephane Cormier
(CRESTIC), Francis Rousseaux (CRESTIC) | Fine-tuning BERT-based models for Plant Health Bulletin Classification | null | Technology and Environment Workshop'21, Jan 2021, Montpellier,
France | null | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In the era of digitization, different actors in agriculture produce numerous
data. Such data contains already latent historical knowledge in the domain.
This knowledge enables us to precisely study natural hazards within global or
local aspects, and then improve the risk prevention tasks and augment the
yield, which ... | [
{
"created": "Fri, 29 Jan 2021 08:14:35 GMT",
"version": "v1"
}
] | 2021-02-02 | [
[
"Jiang",
"Shufan",
"",
"CRESTIC, ISEP"
],
[
"Angarita",
"Rafael",
"",
"ISEP"
],
[
"Cormier",
"Stephane",
"",
"CRESTIC"
],
[
"Rousseaux",
"Francis",
"",
"CRESTIC"
]
] |
2102.00841 | Alexander Sagel | Alexander Sagel, Julian W\"ormann, Hao Shen | Dynamic Texture Recognition via Nuclear Distances on Kernelized
Scattering Histogram Spaces | \c{opyright} 2021 IEEE. Personal use of this material is permitted.
Permission from IEEE must be obtained for all other uses, in any current or
future media, including reprinting/republishing this material for advertising
or promotional purposes, creating new collective works, for resale or
redistribution to se... | ICASSP 2021 - 2021 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP) | 10.1109/ICASSP39728.2021.9414783 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Distance-based dynamic texture recognition is an important research field in
multimedia processing with applications ranging from retrieval to segmentation
of video data. Based on the conjecture that the most distinctive characteristic
of a dynamic texture is the appearance of its individual frames, this work
propose... | [
{
"created": "Mon, 1 Feb 2021 13:54:24 GMT",
"version": "v1"
}
] | 2021-05-17 | [
[
"Sagel",
"Alexander",
""
],
[
"Wörmann",
"Julian",
""
],
[
"Shen",
"Hao",
""
]
] |
2102.00881 | G\"ul\c{s}en Eryi\u{g}it | G\"ul\c{s}en Eryi\u{g}it, Ali \c{S}enta\c{s}, Johanna Monti | Gamified Crowdsourcing for Idiom Corpora Construction | 25 pages, 8 figures, 6 tables | Natural Language Engineering, Cambridge Press, 2022 | 10.1017/S1351324921000401 | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Learning idiomatic expressions is seen as one of the most challenging stages
in second language learning because of their unpredictable meaning. A similar
situation holds for their identification within natural language processing
applications such as machine translation and parsing. The lack of high-quality
usage sa... | [
{
"created": "Mon, 1 Feb 2021 14:44:43 GMT",
"version": "v1"
}
] | 2022-01-21 | [
[
"Eryiğit",
"Gülşen",
""
],
[
"Şentaş",
"Ali",
""
],
[
"Monti",
"Johanna",
""
]
] |
2102.00898 | Mohit Sewak | Mohit Sewak and Sanjay K. Sahay and Hemant Rathore | DRLDO: A novel DRL based De-ObfuscationSystem for Defense against
Metamorphic Malware | null | Defence Science Journal, 71(1), 55-65 | 10.14429/dsj.71.15780 | null | cs.CR cs.AI cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we propose a novel mechanism to normalize metamorphic and
obfuscated malware down at the opcode level and hence create an advanced
metamorphic malware de-obfuscation and defense system. We name this system
DRLDO, for Deep Reinforcement Learning based De-Obfuscator. With the inclusion
of the DRLDO as a ... | [
{
"created": "Mon, 1 Feb 2021 15:16:18 GMT",
"version": "v1"
}
] | 2021-02-02 | [
[
"Sewak",
"Mohit",
""
],
[
"Sahay",
"Sanjay K.",
""
],
[
"Rathore",
"Hemant",
""
]
] |
2102.00997 | Gorka Azkune | Aitzol Elu, Gorka Azkune, Oier Lopez de Lacalle, Ignacio
Arganda-Carreras, Aitor Soroa, Eneko Agirre | Inferring spatial relations from textual descriptions of images | Accepted in Pattern Recognition | Pattern Recognition, Volume 113, 2021, 107847 | 10.1016/j.patcog.2021.107847 | null | cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Generating an image from its textual description requires both a certain
level of language understanding and common sense knowledge about the spatial
relations of the physical entities being described. In this work, we focus on
inferring the spatial relation between entities, a key step in the process of
composing sc... | [
{
"created": "Mon, 1 Feb 2021 17:21:13 GMT",
"version": "v1"
}
] | 2021-02-03 | [
[
"Elu",
"Aitzol",
""
],
[
"Azkune",
"Gorka",
""
],
[
"de Lacalle",
"Oier Lopez",
""
],
[
"Arganda-Carreras",
"Ignacio",
""
],
[
"Soroa",
"Aitor",
""
],
[
"Agirre",
"Eneko",
""
]
] |
2102.01013 | Valentin Pelloin | Valentin Pelloin, Nathalie Camelin, Antoine Laurent, Renato De Mori,
Antoine Caubri\`ere, Yannick Est\`eve, Sylvain Meignier | End2End Acoustic to Semantic Transduction | Accepted at IEEE ICASSP 2021 | ICASSP 2021 - 2021 IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP) | 10.1109/ICASSP39728.2021.9413581 | null | cs.CL cs.SD eess.AS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we propose a novel end-to-end sequence-to-sequence spoken
language understanding model using an attention mechanism. It reliably selects
contextual acoustic features in order to hypothesize semantic contents. An
initial architecture capable of extracting all pronounced words and concepts
from acoustic ... | [
{
"created": "Mon, 1 Feb 2021 17:42:59 GMT",
"version": "v1"
}
] | 2021-05-20 | [
[
"Pelloin",
"Valentin",
""
],
[
"Camelin",
"Nathalie",
""
],
[
"Laurent",
"Antoine",
""
],
[
"De Mori",
"Renato",
""
],
[
"Caubrière",
"Antoine",
""
],
[
"Estève",
"Yannick",
""
],
[
"Meignier",
"Sylvain",
"... |
2102.01149 | Devorah Kletenik | Lisa Hellerstein, Devorah Kletenik and Srinivasan Parthasarathy | A Tight Bound for Stochastic Submodular Cover | This work extends the result of Srinivasan Parthasarathy in his paper
arXiv:1803.07639 from the problem of Stochastic Set Cover to that of
Stochastic Submodular Cover | Journal of Artificial Intelligence Research 71(2021) 347 - 370 | 10.1613/jair.1.12368 | null | cs.DS cs.AI | http://creativecommons.org/licenses/by-nc-sa/4.0/ | We show that the Adaptive Greedy algorithm of Golovin and Krause (2011)
achieves an approximation bound of $(\ln (Q/\eta)+1)$ for Stochastic Submodular
Cover: here $Q$ is the "goal value" and $\eta$ is the smallest non-zero
marginal increase in utility deliverable by an item. (For integer-valued
utility functions, we... | [
{
"created": "Mon, 1 Feb 2021 20:37:40 GMT",
"version": "v1"
},
{
"created": "Mon, 2 Aug 2021 04:26:17 GMT",
"version": "v2"
}
] | 2021-08-03 | [
[
"Hellerstein",
"Lisa",
""
],
[
"Kletenik",
"Devorah",
""
],
[
"Parthasarathy",
"Srinivasan",
""
]
] |
2102.01260 | Xiong Liu | Xiong Liu, Craig E. Thomas, Christian C. Felder | The impact of external innovation on new drug approvals: A retrospective
analysis | null | International Journal of Pharmaceutics, Volume 563, Pages 273-281,
2019 | 10.1016/j.ijpharm.2018.12.093 | PMID: 30664998 | cs.CL cs.CY q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Pharmaceutical companies are relying more often on external sources of
innovation to boost their discovery research productivity. However, more
in-depth knowledge about how external innovation may translate to successful
product launches is still required in order to better understand how to best
leverage the innovat... | [
{
"created": "Tue, 2 Feb 2021 02:21:34 GMT",
"version": "v1"
}
] | 2021-02-03 | [
[
"Liu",
"Xiong",
""
],
[
"Thomas",
"Craig E.",
""
],
[
"Felder",
"Christian C.",
""
]
] |
2102.01284 | Peng Yao | Peng Yao, Shuwei Shen, Mengjuan Xu, Peng Liu, Fan Zhang, Jinyu Xing,
Pengfei Shao, Benjamin Kaffenberger, and Ronald X. Xu | Single Model Deep Learning on Imbalanced Small Datasets for Skin Lesion
Classification | null | IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021 | 10.1109/TMI.2021.3136682 | null | cs.CV cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Deep convolutional neural network (DCNN) models have been widely explored for
skin disease diagnosis and some of them have achieved the diagnostic outcomes
comparable or even superior to those of dermatologists. However, broad
implementation of DCNN in skin disease detection is hindered by small size and
data imbalan... | [
{
"created": "Tue, 2 Feb 2021 03:48:55 GMT",
"version": "v1"
},
{
"created": "Fri, 11 Feb 2022 08:40:10 GMT",
"version": "v2"
}
] | 2022-02-14 | [
[
"Yao",
"Peng",
""
],
[
"Shen",
"Shuwei",
""
],
[
"Xu",
"Mengjuan",
""
],
[
"Liu",
"Peng",
""
],
[
"Zhang",
"Fan",
""
],
[
"Xing",
"Jinyu",
""
],
[
"Shao",
"Pengfei",
""
],
[
"Kaffenberger",
"Ben... |
2102.01295 | Heecheol Kim | Heecheol Kim, Yoshiyuki Ohmura, and Yasuo Kuniyoshi | Gaze-based dual resolution deep imitation learning for high-precision
dexterous robot manipulation | 8 pages. The supplementary video can be found at:
https://www.youtube.com/watch?v=ytpChcFqD5g Published in IEEE Robotics and
Automation Letters. Replaced to add video url in the manuscript | IEEE Robotics and Automation Letters, Vol. 6, No. 2, 2021 | 10.1109/LRA.2021.3059619 | null | cs.RO cs.AI | http://creativecommons.org/licenses/by-nc-nd/4.0/ | A high-precision manipulation task, such as needle threading, is challenging.
Physiological studies have proposed connecting low-resolution peripheral vision
and fast movement to transport the hand into the vicinity of an object, and
using high-resolution foveated vision to achieve the accurate homing of the
hand to ... | [
{
"created": "Tue, 2 Feb 2021 04:11:09 GMT",
"version": "v1"
},
{
"created": "Wed, 3 Mar 2021 03:50:20 GMT",
"version": "v2"
},
{
"created": "Mon, 26 Feb 2024 10:09:46 GMT",
"version": "v3"
}
] | 2024-02-27 | [
[
"Kim",
"Heecheol",
""
],
[
"Ohmura",
"Yoshiyuki",
""
],
[
"Kuniyoshi",
"Yasuo",
""
]
] |
2102.01301 | Yi-Jun Cao | Yi-Jun Cao, Chuan Lin, and Yong-Jie Li | Learning Crisp Boundaries Using Deep Refinement Network and Adaptive
Weighting Loss | 11 pages, 7 figures | IEEE Transactions on Multimedia, vol. 23, pp. 761-771, 2021 | 10.1109/TED.2020.3041567 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Significant progress has been made in boundary detection with the help of
convolutional neural networks. Recent boundary detection models not only focus
on real object boundary detection but also "crisp" boundaries (precisely
localized along the object's contour). There are two methods to evaluate crisp
boundary perf... | [
{
"created": "Tue, 2 Feb 2021 04:22:35 GMT",
"version": "v1"
},
{
"created": "Wed, 3 Mar 2021 07:15:10 GMT",
"version": "v2"
}
] | 2021-03-10 | [
[
"Cao",
"Yi-Jun",
""
],
[
"Lin",
"Chuan",
""
],
[
"Li",
"Yong-Jie",
""
]
] |
2102.01380 | Zhong Meng | Zhong Meng, Naoyuki Kanda, Yashesh Gaur, Sarangarajan Parthasarathy,
Eric Sun, Liang Lu, Xie Chen, Jinyu Li, Yifan Gong | Internal Language Model Training for Domain-Adaptive End-to-End Speech
Recognition | 5 pages, ICASSP 2021 | 2021 IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP), Toronto, Canada | null | null | eess.AS cs.AI cs.CL cs.LG cs.SD | http://creativecommons.org/licenses/by/4.0/ | The efficacy of external language model (LM) integration with existing
end-to-end (E2E) automatic speech recognition (ASR) systems can be improved
significantly using the internal language model estimation (ILME) method. In
this method, the internal LM score is subtracted from the score obtained by
interpolating the ... | [
{
"created": "Tue, 2 Feb 2021 08:15:02 GMT",
"version": "v1"
},
{
"created": "Thu, 22 Apr 2021 19:16:04 GMT",
"version": "v2"
}
] | 2021-04-26 | [
[
"Meng",
"Zhong",
""
],
[
"Kanda",
"Naoyuki",
""
],
[
"Gaur",
"Yashesh",
""
],
[
"Parthasarathy",
"Sarangarajan",
""
],
[
"Sun",
"Eric",
""
],
[
"Lu",
"Liang",
""
],
[
"Chen",
"Xie",
""
],
[
"Li",
... |
2102.01405 | Ruben Tolosana | Ruben Tolosana, Juan Carlos Ruiz-Garcia, Ruben Vera-Rodriguez, Jaime
Herreros-Rodriguez, Sergio Romero-Tapiador, Aythami Morales, Julian Fierrez | Child-Computer Interaction with Mobile Devices: Recent Works, New
Dataset, and Age Detection | null | IEEE Transactions on Emerging Topics in Computing, 2022 | 10.1109/TETC.2022.3150836 | null | cs.HC cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | This article provides an overview of recent research in Child-Computer
Interaction with mobile devices and describe our framework ChildCI intended
for: i) overcoming the lack of large-scale publicly available databases in the
area, ii) generating a better understanding of the cognitive and neuromotor
development of c... | [
{
"created": "Tue, 2 Feb 2021 09:51:58 GMT",
"version": "v1"
},
{
"created": "Mon, 21 Feb 2022 08:57:57 GMT",
"version": "v2"
},
{
"created": "Tue, 22 Feb 2022 08:38:02 GMT",
"version": "v3"
}
] | 2022-02-23 | [
[
"Tolosana",
"Ruben",
""
],
[
"Ruiz-Garcia",
"Juan Carlos",
""
],
[
"Vera-Rodriguez",
"Ruben",
""
],
[
"Herreros-Rodriguez",
"Jaime",
""
],
[
"Romero-Tapiador",
"Sergio",
""
],
[
"Morales",
"Aythami",
""
],
[
"Fierr... |
2102.01460 | Alberto Pretto | Alessandro Saviolo, Matteo Bonotto, Daniele Evangelista, Marco
Imperoli, Jacopo Lazzaro, Emanuele Menegatti and Alberto Pretto | Learning to Segment Human Body Parts with Synthetically Trained Deep
Convolutional Networks | This paper has been published in: Proceedings of the 16th
International Conference on Intelligent Autonomous Systems (IAS 2021) | Proceedings of the 16th International Conference on Intelligent
Autonomous Systems (IAS 2021) | 10.1007/978-3-030-95892-3_52 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper presents a new framework for human body part segmentation based on
Deep Convolutional Neural Networks trained using only synthetic data. The
proposed approach achieves cutting-edge results without the need of training
the models with real annotated data of human body parts. Our contributions
include a data... | [
{
"created": "Tue, 2 Feb 2021 12:26:50 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Nov 2021 15:06:02 GMT",
"version": "v2"
},
{
"created": "Tue, 7 Jun 2022 15:10:20 GMT",
"version": "v3"
}
] | 2022-06-08 | [
[
"Saviolo",
"Alessandro",
""
],
[
"Bonotto",
"Matteo",
""
],
[
"Evangelista",
"Daniele",
""
],
[
"Imperoli",
"Marco",
""
],
[
"Lazzaro",
"Jacopo",
""
],
[
"Menegatti",
"Emanuele",
""
],
[
"Pretto",
"Alberto",
... |
2102.01486 | Cheng Ma | Cheng Ma, Jiwen Lu, Jie Zhou | Rank-Consistency Deep Hashing for Scalable Multi-Label Image Search | null | IEEE Transactions on Multimedia, 2020 | 10.1109/TMM.2020.3034534 | null | cs.CV cs.MM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | As hashing becomes an increasingly appealing technique for large-scale image
retrieval, multi-label hashing is also attracting more attention for the
ability to exploit multi-level semantic contents. In this paper, we propose a
novel deep hashing method for scalable multi-label image search. Unlike
existing approache... | [
{
"created": "Tue, 2 Feb 2021 13:46:58 GMT",
"version": "v1"
}
] | 2021-02-03 | [
[
"Ma",
"Cheng",
""
],
[
"Lu",
"Jiwen",
""
],
[
"Zhou",
"Jie",
""
]
] |
2102.01498 | Iuliana Marin | Andrei Vasilateanu, Nicolae Goga, Elena-Alice Tanase, Iuliana Marin | Enterprise domain ontology learning from web-based corpus | null | 2015 6th International Conference on Computing, Communication and
Networking Technologies (ICCCNT) | 10.1109/ICCCNT.2015.7395227 | null | cs.AI cs.SE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Enterprise knowledge is a key asset in the competing and fast-changing
corporate landscape. The ability to learn, store and distribute implicit and
explicit knowledge can be the difference between success and failure. While
enterprise knowledge management is a well-defined research domain, current
implementations lac... | [
{
"created": "Fri, 29 Jan 2021 17:08:29 GMT",
"version": "v1"
}
] | 2021-02-16 | [
[
"Vasilateanu",
"Andrei",
""
],
[
"Goga",
"Nicolae",
""
],
[
"Tanase",
"Elena-Alice",
""
],
[
"Marin",
"Iuliana",
""
]
] |
2102.01502 | Satyapriya Krishna | Satyapriya Krishna, Rahul Gupta, Christophe Dupuy | ADePT: Auto-encoder based Differentially Private Text Transformation | null | The 16th conference of the European Chapter of the Association for
Computational Linguistics (EACL), 2021 | null | null | cs.CR cs.AI cs.CL cs.LG | http://creativecommons.org/licenses/by/4.0/ | Privacy is an important concern when building statistical models on data
containing personal information. Differential privacy offers a strong
definition of privacy and can be used to solve several privacy concerns (Dwork
et al., 2014). Multiple solutions have been proposed for the
differentially-private transformati... | [
{
"created": "Fri, 29 Jan 2021 23:15:24 GMT",
"version": "v1"
}
] | 2021-02-03 | [
[
"Krishna",
"Satyapriya",
""
],
[
"Gupta",
"Rahul",
""
],
[
"Dupuy",
"Christophe",
""
]
] |
2102.01565 | Juan Pedro Dominguez-Morales | Luis J. Mu\~noz-Molina, Ignacio Cazorla-Pi\~nar, Juan P.
Dominguez-Morales, Fernando Perez-Pe\~na | Real-time detection of uncalibrated sensors using Neural Networks | null | Neural Comput & Applic (2022) | 10.1007/s00521-021-06865-z | null | cs.LG cs.AI | http://creativecommons.org/licenses/by/4.0/ | Nowadays, sensors play a major role in several contexts like science,
industry and daily life which benefit of their use. However, the retrieved
information must be reliable. Anomalies in the behavior of sensors can give
rise to critical consequences such as ruining a scientific project or
jeopardizing the quality of... | [
{
"created": "Tue, 2 Feb 2021 15:44:39 GMT",
"version": "v1"
}
] | 2022-01-26 | [
[
"Muñoz-Molina",
"Luis J.",
""
],
[
"Cazorla-Piñar",
"Ignacio",
""
],
[
"Dominguez-Morales",
"Juan P.",
""
],
[
"Perez-Peña",
"Fernando",
""
]
] |
2102.01578 | Marco Gaido | Marco Gaido, Mauro Cettolo, Matteo Negri, Marco Turchi | CTC-based Compression for Direct Speech Translation | Accepted at EACL2021 | Proceedings of the 16th Conference of the European Chapter of the
Association for Computational Linguistics: Main Volume (2021), 690-696 | null | null | cs.CL | http://creativecommons.org/licenses/by-sa/4.0/ | Previous studies demonstrated that a dynamic phone-informed compression of
the input audio is beneficial for speech translation (ST). However, they
required a dedicated model for phone recognition and did not test this solution
for direct ST, in which a single model translates the input audio into the
target language... | [
{
"created": "Tue, 2 Feb 2021 16:09:19 GMT",
"version": "v1"
}
] | 2021-10-15 | [
[
"Gaido",
"Marco",
""
],
[
"Cettolo",
"Mauro",
""
],
[
"Negri",
"Matteo",
""
],
[
"Turchi",
"Marco",
""
]
] |
2102.01579 | Xiangyu Xu | Xiangyu Xu, Yongrui Ma, Wenxiu Sun, Ming-Hsuan Yang | Exploiting Raw Images for Real-Scene Super-Resolution | A larger version with higher-resolution figures is available at:
https://sites.google.com/view/xiangyuxu. arXiv admin note: text overlap with
arXiv:1905.12156 | IEEE Transactions on Pattern Analysis and Machine Intelligence,
2020 | null | null | cs.CV cs.AI | http://creativecommons.org/licenses/by/4.0/ | Super-resolution is a fundamental problem in computer vision which aims to
overcome the spatial limitation of camera sensors. While significant progress
has been made in single image super-resolution, most algorithms only perform
well on synthetic data, which limits their applications in real scenarios. In
this paper... | [
{
"created": "Tue, 2 Feb 2021 16:10:15 GMT",
"version": "v1"
}
] | 2021-02-03 | [
[
"Xu",
"Xiangyu",
""
],
[
"Ma",
"Yongrui",
""
],
[
"Sun",
"Wenxiu",
""
],
[
"Yang",
"Ming-Hsuan",
""
]
] |
2102.01582 | Mats Richter | Mats L. Richter, Wolf Byttner, Ulf Krumnack, Ludwdig Schallner, Justin
Shenk | Size Matters | Preprint | Artificial Neural Networks and Machine Learning ICANN 2021 133-144 | 10.1007/978-3-030-86340-1_11 | null | cs.LG cs.AI cs.CV | http://creativecommons.org/licenses/by/4.0/ | Fully convolutional neural networks can process input of arbitrary size by
applying a combination of downsampling and pooling. However, we find that fully
convolutional image classifiers are not agnostic to the input size but rather
show significant differences in performance: presenting the same image at
different s... | [
{
"created": "Tue, 2 Feb 2021 16:17:52 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Feb 2021 09:00:14 GMT",
"version": "v2"
}
] | 2021-10-13 | [
[
"Richter",
"Mats L.",
""
],
[
"Byttner",
"Wolf",
""
],
[
"Krumnack",
"Ulf",
""
],
[
"Schallner",
"Ludwdig",
""
],
[
"Shenk",
"Justin",
""
]
] |
2102.01645 | Federico Galatolo | Federico A. Galatolo and Mario G.C.A. Cimino and Gigliola Vaglini | Generating images from caption and vice versa via CLIP-Guided Generative
Latent Space Search | null | IMPROVE, ISBN 978-989-758-511-1, pages 166-174 (2021) | 10.5220/0010503701660174 | null | cs.NE cs.AI cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this research work we present CLIP-GLaSS, a novel zero-shot framework to
generate an image (or a caption) corresponding to a given caption (or image).
CLIP-GLaSS is based on the CLIP neural network, which, given an image and a
descriptive caption, provides similar embeddings. Differently, CLIP-GLaSS takes
a captio... | [
{
"created": "Tue, 2 Feb 2021 18:00:13 GMT",
"version": "v1"
},
{
"created": "Wed, 3 Feb 2021 12:14:49 GMT",
"version": "v2"
},
{
"created": "Fri, 26 Feb 2021 22:42:49 GMT",
"version": "v3"
},
{
"created": "Fri, 1 Oct 2021 15:45:51 GMT",
"version": "v4"
}
] | 2021-10-04 | [
[
"Galatolo",
"Federico A.",
""
],
[
"Cimino",
"Mario G. C. A.",
""
],
[
"Vaglini",
"Gigliola",
""
]
] |
2102.01767 | Jorge Miguel Ferreira Da Silva | Jorge Miguel Silva, Diogo Pratas, Rui Antunes, S\'ergio Matos, and
Armando J. Pinho | Automatic analysis of artistic paintings using information-based
measures | Website: http://panther.web.ua.pt 24 Pages; 19 pages article; 5 pages
supplementary material | Pattern Recognition (2021) 107864 | 10.1016/j.patcog.2021.107864 | null | cs.CV cs.IT cs.LG math.IT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The artistic community is increasingly relying on automatic computational
analysis for authentication and classification of artistic paintings. In this
paper, we identify hidden patterns and relationships present in artistic
paintings by analysing their complexity, a measure that quantifies the sum of
characteristics... | [
{
"created": "Tue, 2 Feb 2021 21:40:30 GMT",
"version": "v1"
}
] | 2021-02-10 | [
[
"Silva",
"Jorge Miguel",
""
],
[
"Pratas",
"Diogo",
""
],
[
"Antunes",
"Rui",
""
],
[
"Matos",
"Sérgio",
""
],
[
"Pinho",
"Armando J.",
""
]
] |
2102.01780 | Daniel Severin Dr. | Mauro Lucci, Daniel Sever\'in, Paula Zabala | A metaheuristic for crew scheduling in a pickup-and-delivery problem
with time windows | null | Intl. Trans. in Op. Res., vol. 30, 2023, pp. 970-1001 | 10.1111/itor.13096 | null | cs.AI cs.DM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A vehicle routing and crew scheduling problem (VRCSP) consists of
simultaneously planning the routes of a fleet of vehicles and scheduling the
crews, where the vehicle-crew correspondence is not fixed through time. This
allows a greater planning flexibility and a more efficient use of the fleet,
but in counterpart, a... | [
{
"created": "Tue, 2 Feb 2021 22:14:10 GMT",
"version": "v1"
}
] | 2024-07-11 | [
[
"Lucci",
"Mauro",
""
],
[
"Severín",
"Daniel",
""
],
[
"Zabala",
"Paula",
""
]
] |
2102.01826 | Zhewei Sun | Zhewei Sun, Richard Zemel, Yang Xu | A Computational Framework for Slang Generation | Accepted for publication in TACL 2021. Author's final version | Transactions of the Association for Computational Linguistics
2021; 9 462-478 | 10.1162/tacl_a_00378 | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Slang is a common type of informal language, but its flexible nature and
paucity of data resources present challenges for existing natural language
systems. We take an initial step toward machine generation of slang by
developing a framework that models the speaker's word choice in slang context.
Our framework encode... | [
{
"created": "Wed, 3 Feb 2021 01:19:07 GMT",
"version": "v1"
},
{
"created": "Sat, 22 May 2021 04:46:48 GMT",
"version": "v2"
}
] | 2021-05-25 | [
[
"Sun",
"Zhewei",
""
],
[
"Zemel",
"Richard",
""
],
[
"Xu",
"Yang",
""
]
] |
2102.01850 | Ru Li | Ru Li, Chuan Wang, Jue Wang, Guanghui Liu, Heng-Yu Zhang, Bing Zeng,
Shuaicheng Liu | UPHDR-GAN: Generative Adversarial Network for High Dynamic Range Imaging
with Unpaired Data | Accepted by IEEE Transactions on Circuits and Systems for Video
Technology (TCSVT) | IEEE Transactions on Circuits and Systems for Video Technology,
2022 | 10.1109/TCSVT.2022.3190057 | null | eess.IV cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The paper proposes a method to effectively fuse multi-exposure inputs and
generate high-quality high dynamic range (HDR) images with unpaired datasets.
Deep learning-based HDR image generation methods rely heavily on paired
datasets. The ground truth images play a leading role in generating reasonable
HDR images. Dat... | [
{
"created": "Wed, 3 Feb 2021 03:09:14 GMT",
"version": "v1"
},
{
"created": "Fri, 15 Jul 2022 07:54:33 GMT",
"version": "v2"
}
] | 2022-07-18 | [
[
"Li",
"Ru",
""
],
[
"Wang",
"Chuan",
""
],
[
"Wang",
"Jue",
""
],
[
"Liu",
"Guanghui",
""
],
[
"Zhang",
"Heng-Yu",
""
],
[
"Zeng",
"Bing",
""
],
[
"Liu",
"Shuaicheng",
""
]
] |
2102.01906 | Vinod Kumar Kurmi | Vinod K Kurmi, Badri N. Patro, Venkatesh K. Subramanian, Vinay P.
Namboodiri | Do Not Forget to Attend to Uncertainty while Mitigating Catastrophic
Forgetting | Accepted WACV 2021 | WACV 2021 | null | null | cs.LG cs.CV | http://creativecommons.org/licenses/by-nc-sa/4.0/ | One of the major limitations of deep learning models is that they face
catastrophic forgetting in an incremental learning scenario. There have been
several approaches proposed to tackle the problem of incremental learning. Most
of these methods are based on knowledge distillation and do not adequately
utilize the inf... | [
{
"created": "Wed, 3 Feb 2021 06:54:52 GMT",
"version": "v1"
}
] | 2021-02-04 | [
[
"Kurmi",
"Vinod K",
""
],
[
"Patro",
"Badri N.",
""
],
[
"Subramanian",
"Venkatesh K.",
""
],
[
"Namboodiri",
"Vinay P.",
""
]
] |
2102.01968 | Claire Theobald | Claire Theobald (LORIA), Fr\'ed\'eric Pennerath (LORIA), Brieuc
Conan-Guez (LORIA), Miguel Couceiro (LORIA), Amedeo Napoli (LORIA) | A Bayesian Neural Network based on Dropout Regulation | null | Workshop on Uncertainty in Machine Learning (WUML) at ECML-PKDD
2020 Conference, Eyke H{\"u}llermeier; S{\'e}bastien Destercke, 2020, N.A.
(online), France | null | null | cs.LG cs.AI cs.NE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Bayesian Neural Networks (BNN) have recently emerged in the Deep Learning
world for dealing with uncertainty estimation in classification tasks, and are
used in many application domains such as astrophysics, autonomous driving...BNN
assume a prior over the weights of a neural network instead of point estimates,
enabl... | [
{
"created": "Wed, 3 Feb 2021 09:39:50 GMT",
"version": "v1"
}
] | 2021-02-04 | [
[
"Theobald",
"Claire",
"",
"LORIA"
],
[
"Pennerath",
"Frédéric",
"",
"LORIA"
],
[
"Conan-Guez",
"Brieuc",
"",
"LORIA"
],
[
"Couceiro",
"Miguel",
"",
"LORIA"
],
[
"Napoli",
"Amedeo",
"",
"LORIA"
]
] |
2102.02189 | Young-Suk Lee Dr. | Janaki Sheth and Young-Suk Lee and Ramon Fernandez Astudillo and
Tahira Naseem and Radu Florian and Salim Roukos and Todd Ward | Bootstrapping Multilingual AMR with Contextual Word Alignments | null | EACL 2021 | null | null | cs.CL cs.AI | http://creativecommons.org/licenses/by-sa/4.0/ | We develop high performance multilingualAbstract Meaning Representation (AMR)
sys-tems by projecting English AMR annotationsto other languages with weak
supervision. Weachieve this goal by bootstrapping transformer-based
multilingual word embeddings, in partic-ular those from cross-lingual RoBERTa
(XLM-R large). We d... | [
{
"created": "Wed, 3 Feb 2021 18:35:55 GMT",
"version": "v1"
}
] | 2022-05-09 | [
[
"Sheth",
"Janaki",
""
],
[
"Lee",
"Young-Suk",
""
],
[
"Astudillo",
"Ramon Fernandez",
""
],
[
"Naseem",
"Tahira",
""
],
[
"Florian",
"Radu",
""
],
[
"Roukos",
"Salim",
""
],
[
"Ward",
"Todd",
""
]
] |
2102.02304 | Panayiotis Danassis | Panayiotis Danassis, Zeki Doruk Erden, Boi Faltings | Improved Cooperation by Exploiting a Common Signal | Accepted to the 20th International Conference on Autonomous Agents
and Multiagent Systems (AAMAS 2021) | An extended version of this paper has been published in the
Autonomous Agents and Multi-Agent Systems (2022) | 10.1007/s10458-021-09541-7 | null | cs.MA cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Can artificial agents benefit from human conventions? Human societies manage
to successfully self-organize and resolve the tragedy of the commons in
common-pool resources, in spite of the bleak prediction of non-cooperative game
theory. On top of that, real-world problems are inherently large-scale and of
low observa... | [
{
"created": "Wed, 3 Feb 2021 21:27:53 GMT",
"version": "v1"
}
] | 2022-03-29 | [
[
"Danassis",
"Panayiotis",
""
],
[
"Erden",
"Zeki Doruk",
""
],
[
"Faltings",
"Boi",
""
]
] |
2102.02585 | V\'it Novotn\'y | V\'it Novotn\'y (1) and Eniafe Festus Ayetiran (1) and Dalibor
Ba\v{c}ovsk\'y (1) and D\'avid Lupt\'ak (1) and Michal \v{S}tef\'anik (1) and
Petr Sojka (1) ((1) Faculty of Informatics Masaryk University) | One Size Does Not Fit All: Finding the Optimal Subword Sizes for
FastText Models across Languages | null | RANLP (2021) 1072-1078 | 10.26615/978-954-452-072-4_121 | null | cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Unsupervised representation learning of words from large multilingual corpora
is useful for downstream tasks such as word sense disambiguation, semantic text
similarity, and information retrieval. The representation precision of
log-bilinear fastText models is mostly due to their use of subword information.
In previo... | [
{
"created": "Thu, 4 Feb 2021 12:59:36 GMT",
"version": "v1"
},
{
"created": "Sat, 21 Aug 2021 12:13:23 GMT",
"version": "v2"
},
{
"created": "Mon, 20 Sep 2021 17:50:51 GMT",
"version": "v3"
}
] | 2021-09-21 | [
[
"Novotný",
"Vít",
"",
"Faculty of Informatics Masaryk University"
],
[
"Ayetiran",
"Eniafe Festus",
"",
"Faculty of Informatics Masaryk University"
],
[
"Bačovský",
"Dalibor",
"",
"Faculty of Informatics Masaryk University"
],
[
"Lupták",
"Dávid"... |
2102.02636 | Hendri Murfi | Hendri Murfi, Natasha Rosaline, Nora Hariadi | Deep Autoencoder-based Fuzzy C-Means for Topic Detection | 18 pages | Array 13 (2022) | 10.1016/j.array.2021.100124 | null | cs.IR cs.CL cs.LG | http://creativecommons.org/licenses/by/4.0/ | Topic detection is a process for determining topics from a collection of
textual data. One of the topic detection methods is a clustering-based method,
which assumes that the centroids are topics. The clustering method has the
advantage that it can process data with negative representations. Therefore,
the clustering... | [
{
"created": "Tue, 2 Feb 2021 07:41:52 GMT",
"version": "v1"
}
] | 2021-12-28 | [
[
"Murfi",
"Hendri",
""
],
[
"Rosaline",
"Natasha",
""
],
[
"Hariadi",
"Nora",
""
]
] |
2102.02711 | Soumick Chatterjee | Chompunuch Sarasaen, Soumick Chatterjee, Mario Breitkopf, Georg Rose,
Andreas N\"urnberger and Oliver Speck | Fine-tuning deep learning model parameters for improved super-resolution
of dynamic MRI with prior-knowledge | null | Artificial Intelligence in Medicine (2021) 102196 | 10.1016/j.artmed.2021.102196 | null | eess.IV cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Dynamic imaging is a beneficial tool for interventions to assess
physiological changes. Nonetheless during dynamic MRI, while achieving a high
temporal resolution, the spatial resolution is compromised. To overcome this
spatio-temporal trade-off, this research presents a super-resolution (SR) MRI
reconstruction with ... | [
{
"created": "Thu, 4 Feb 2021 16:11:53 GMT",
"version": "v1"
},
{
"created": "Fri, 23 Apr 2021 12:24:51 GMT",
"version": "v2"
},
{
"created": "Sat, 4 Sep 2021 21:25:18 GMT",
"version": "v3"
},
{
"created": "Sat, 23 Oct 2021 10:42:29 GMT",
"version": "v4"
}
] | 2021-10-26 | [
[
"Sarasaen",
"Chompunuch",
""
],
[
"Chatterjee",
"Soumick",
""
],
[
"Breitkopf",
"Mario",
""
],
[
"Rose",
"Georg",
""
],
[
"Nürnberger",
"Andreas",
""
],
[
"Speck",
"Oliver",
""
]
] |
2102.02771 | Jun Wang | Jun Wang, Xiaohan Yu, Yongsheng Gao | Mask Guided Attention For Fine-Grained Patchy Image Classification | Accepted to ICIP2021 | 2021 IEEE International Conference on Image Processing (ICIP),
2021, pp. 1044-1048 | 10.1109/ICIP42928.2021.9506424 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work, we present a novel mask guided attention (MGA) method for
fine-grained patchy image classification. The key challenge of fine-grained
patchy image classification lies in two folds, ultra-fine-grained
inter-category variances among objects and very few data available for
training. This motivates us to co... | [
{
"created": "Thu, 4 Feb 2021 17:54:50 GMT",
"version": "v1"
},
{
"created": "Wed, 22 Sep 2021 10:09:32 GMT",
"version": "v2"
}
] | 2021-09-23 | [
[
"Wang",
"Jun",
""
],
[
"Yu",
"Xiaohan",
""
],
[
"Gao",
"Yongsheng",
""
]
] |
2102.02789 | Vivien Cabannes | Vivien Cabannes, Francis Bach, Alessandro Rudi | Disambiguation of weak supervision with exponential convergence rates | 22 pages; 6 figures | Proceedings of the 38th International Conference on Machine
Learning, PMLR 139, 2021 | null | null | cs.LG cs.AI stat.ML | http://creativecommons.org/licenses/by/4.0/ | Machine learning approached through supervised learning requires expensive
annotation of data. This motivates weakly supervised learning, where data are
annotated with incomplete yet discriminative information. In this paper, we
focus on partial labelling, an instance of weak supervision where, from a given
input, we... | [
{
"created": "Thu, 4 Feb 2021 18:14:32 GMT",
"version": "v1"
},
{
"created": "Wed, 26 May 2021 16:14:29 GMT",
"version": "v2"
},
{
"created": "Thu, 15 Jul 2021 14:29:24 GMT",
"version": "v3"
}
] | 2021-07-16 | [
[
"Cabannes",
"Vivien",
""
],
[
"Bach",
"Francis",
""
],
[
"Rudi",
"Alessandro",
""
]
] |
2102.02887 | Shiwei Liu | Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy | Do We Actually Need Dense Over-Parameterization? In-Time
Over-Parameterization in Sparse Training | 16 pages; 10 figures; Published in Proceedings of the 38th
International Conference on Machine Learning. Code can be found
https://github.com/Shiweiliuiiiiiii/In-Time-Over-Parameterization | Proceedings of the 38th International Conference on Machine
Learning (2021) | null | null | cs.LG cs.AI cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we introduce a new perspective on training deep neural
networks capable of state-of-the-art performance without the need for the
expensive over-parameterization by proposing the concept of In-Time
Over-Parameterization (ITOP) in sparse training. By starting from a random
sparse network and continuously... | [
{
"created": "Thu, 4 Feb 2021 20:59:31 GMT",
"version": "v1"
},
{
"created": "Sat, 13 Feb 2021 23:36:57 GMT",
"version": "v2"
},
{
"created": "Tue, 15 Jun 2021 05:01:46 GMT",
"version": "v3"
}
] | 2021-06-16 | [
[
"Liu",
"Shiwei",
""
],
[
"Yin",
"Lu",
""
],
[
"Mocanu",
"Decebal Constantin",
""
],
[
"Pechenizkiy",
"Mykola",
""
]
] |
2102.02917 | Allison Lahnala | Allison Lahnala, Gauri Kambhatla, Jiajun Peng, Matthew Whitehead,
Gillian Minnehan, Eric Guldan, Jonathan K. Kummerfeld, An{\i}l \c{C}amc{\i},
Rada Mihalcea | Chord Embeddings: Analyzing What They Capture and Their Role for Next
Chord Prediction and Artist Attribute Prediction | 16 pages, accepted to EvoMUSART | Computational Intelligence in Music, Sound, Art and Design, 10th
International Conference, EvoMUSART 2021 | null | null | cs.SD cs.AI cs.CL | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Natural language processing methods have been applied in a variety of music
studies, drawing the connection between music and language. In this paper, we
expand those approaches by investigating \textit{chord embeddings}, which we
apply in two case studies to address two key questions: (1) what musical
information do... | [
{
"created": "Thu, 4 Feb 2021 22:17:17 GMT",
"version": "v1"
}
] | 2021-02-08 | [
[
"Lahnala",
"Allison",
""
],
[
"Kambhatla",
"Gauri",
""
],
[
"Peng",
"Jiajun",
""
],
[
"Whitehead",
"Matthew",
""
],
[
"Minnehan",
"Gillian",
""
],
[
"Guldan",
"Eric",
""
],
[
"Kummerfeld",
"Jonathan K.",
""... |
2102.03022 | Tim Miller | Zhengshang Liu, Yue Yang, Tim Miller, and Peta Masters | Deceptive Reinforcement Learning for Privacy-Preserving Planning | null | Proceedings of the 20th International Conference on Autonomous
Agents and Multiagent Systems (AAMAS 2021) | null | null | cs.LG cs.AI cs.MA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we study the problem of deceptive reinforcement learning to
preserve the privacy of a reward function. Reinforcement learning is the
problem of finding a behaviour policy based on rewards received from
exploratory behaviour. A key ingredient in reinforcement learning is a reward
function, which determi... | [
{
"created": "Fri, 5 Feb 2021 06:50:04 GMT",
"version": "v1"
}
] | 2021-02-08 | [
[
"Liu",
"Zhengshang",
""
],
[
"Yang",
"Yue",
""
],
[
"Miller",
"Tim",
""
],
[
"Masters",
"Peta",
""
]
] |
2102.03049 | Shang Ran Huang | Fu-Shun Hsu, Shang-Ran Huang, Chien-Wen Huang, Chao-Jung Huang,
Yuan-Ren Cheng, Chun-Chieh Chen, Jack Hsiao, Chung-Wei Chen, Li-Chin Chen,
Yen-Chun Lai, Bi-Fang Hsu, Nian-Jhen Lin, Wan-Lin Tsai, Yi-Lin Wu, Tzu-Ling
Tseng, Ching-Ting Tseng, Yi-Tsun Chen, Feipei Lai | Benchmarking of eight recurrent neural network variants for breath phase
and adventitious sound detection on a self-developed open-access lung sound
database-HF_Lung_V1 | 48 pages, 8 figures. Accepted by PLoS One | PLoS ONE, 2021, 16(7): e0254134 | 10.1371/journal.pone.0254134 | null | cs.SD cs.AI cs.LG eess.AS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A reliable, remote, and continuous real-time respiratory sound monitor with
automated respiratory sound analysis ability is urgently required in many
clinical scenarios-such as in monitoring disease progression of coronavirus
disease 2019-to replace conventional auscultation with a handheld stethoscope.
However, a ro... | [
{
"created": "Fri, 5 Feb 2021 08:21:28 GMT",
"version": "v1"
},
{
"created": "Wed, 3 Mar 2021 15:22:55 GMT",
"version": "v2"
},
{
"created": "Tue, 12 Jul 2022 09:04:06 GMT",
"version": "v3"
}
] | 2022-07-13 | [
[
"Hsu",
"Fu-Shun",
""
],
[
"Huang",
"Shang-Ran",
""
],
[
"Huang",
"Chien-Wen",
""
],
[
"Huang",
"Chao-Jung",
""
],
[
"Cheng",
"Yuan-Ren",
""
],
[
"Chen",
"Chun-Chieh",
""
],
[
"Hsiao",
"Jack",
""
],
[
... |
2102.03277 | Llu\'is Alemany-Puig | Llu\'is Alemany-Puig, Juan Luis Esteban, Ramon Ferrer-i-Cancho | Minimum projective linearizations of trees in linear time | Here we have corrected a mistake we made in the previous version. In
particular, line 7 of Algorithm 3.2 used to say: "For i = 1 to |C_v| ..."; it
should be "For i = 2 to |C_v| ..." (notice the change from 'i=1' to 'i=2') | Information Processing Letters, 174:106204 (2022) | 10.1016/j.ipl.2021.106204 | null | cs.DS cs.CL cs.DM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Minimum Linear Arrangement problem (MLA) consists of finding a mapping
$\pi$ from vertices of a graph to distinct integers that minimizes
$\sum_{\{u,v\}\in E}|\pi(u) - \pi(v)|$. In that setting, vertices are often
assumed to lie on a horizontal line and edges are drawn as semicircles above
said line. For trees, v... | [
{
"created": "Fri, 5 Feb 2021 16:35:38 GMT",
"version": "v1"
},
{
"created": "Wed, 17 Feb 2021 14:20:33 GMT",
"version": "v2"
},
{
"created": "Mon, 26 Jul 2021 14:02:41 GMT",
"version": "v3"
},
{
"created": "Wed, 8 Sep 2021 15:19:02 GMT",
"version": "v4"
},
{
"cre... | 2024-09-13 | [
[
"Alemany-Puig",
"Lluís",
""
],
[
"Esteban",
"Juan Luis",
""
],
[
"Ferrer-i-Cancho",
"Ramon",
""
]
] |
2102.03310 | Michal Ciszewski | Micha{\l} Ciszewski, Jakob S\"ohl, Geurt Jongbloed | Improving state estimation through projection post-processing for
activity recognition with application to football | This preprint has not undergone peer review (when applicable) or any
post-submission improvements or corrections. The Version of Record of this
article is published in Statistical Methods & Applications, and is available
online at https://doi.org/10.1007/s10260-023-00696-z | Stat Methods Appl (2023) | 10.1007/s10260-023-00696-z | null | cs.CV | http://creativecommons.org/licenses/by/4.0/ | The past decade has seen an increased interest in human activity recognition
based on sensor data. Most often, the sensor data come unannotated, creating
the need for fast labelling methods. For assessing the quality of the
labelling, an appropriate performance measure has to be chosen. Our main
contribution is a nov... | [
{
"created": "Fri, 5 Feb 2021 17:32:39 GMT",
"version": "v1"
},
{
"created": "Thu, 10 Jun 2021 09:43:01 GMT",
"version": "v2"
},
{
"created": "Fri, 2 Sep 2022 10:27:28 GMT",
"version": "v3"
},
{
"created": "Tue, 2 May 2023 19:56:30 GMT",
"version": "v4"
}
] | 2023-05-04 | [
[
"Ciszewski",
"Michał",
""
],
[
"Söhl",
"Jakob",
""
],
[
"Jongbloed",
"Geurt",
""
]
] |
2102.03380 | Manuel L\'opez-Ib\'a\~nez | Manuel L\'opez-Ib\'a\~nez (University of M\'alaga, Spain), Juergen
Branke (University of Warwick, UK), Lu\'is Paquete (University of Coimbra,
Portugal) | Reproducibility in Evolutionary Computation | null | ACM Transactions on Evolutionary Learning and Optimization, 2021 | 10.1145/3466624 | null | cs.AI cs.NE math.OC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Experimental studies are prevalent in Evolutionary Computation (EC), and
concerns about the reproducibility and replicability of such studies have
increased in recent times, reflecting similar concerns in other scientific
fields. In this article, we discuss, within the context of EC, the different
types of reproducib... | [
{
"created": "Fri, 5 Feb 2021 19:06:35 GMT",
"version": "v1"
},
{
"created": "Tue, 29 Jun 2021 16:24:25 GMT",
"version": "v2"
}
] | 2022-03-30 | [
[
"López-Ibáñez",
"Manuel",
"",
"University of Málaga, Spain"
],
[
"Branke",
"Juergen",
"",
"University of Warwick, UK"
],
[
"Paquete",
"Luís",
"",
"University of Coimbra,\n Portugal"
]
] |
2102.03382 | Tu Le | Tu Le, Danny Yuxing Huang, Noah Apthorpe, Yuan Tian | SkillBot: Identifying Risky Content for Children in Alexa Skills | null | ACM Transactions on Internet Technology, Volume 22, Issue 3,
August 2022, Article 79, pp 1-31 | 10.1145/3539609 | null | cs.MA cs.CL cs.CR cs.HC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Many households include children who use voice personal assistants (VPA) such
as Amazon Alexa. Children benefit from the rich functionalities of VPAs and
third-party apps but are also exposed to new risks in the VPA ecosystem. In
this paper, we first investigate "risky" child-directed voice apps that contain
inapprop... | [
{
"created": "Fri, 5 Feb 2021 19:07:39 GMT",
"version": "v1"
},
{
"created": "Thu, 2 Jun 2022 02:28:15 GMT",
"version": "v2"
}
] | 2022-10-13 | [
[
"Le",
"Tu",
""
],
[
"Huang",
"Danny Yuxing",
""
],
[
"Apthorpe",
"Noah",
""
],
[
"Tian",
"Yuan",
""
]
] |
2102.03419 | Dora Jambor | Dora Jambor, Komal Teru, Joelle Pineau, William L. Hamilton | Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs | code available at
https://github.com/dorajam/few-shot-link-prediction-paper | European Chapter of the ACL (EACL), 2021 | null | null | cs.AI cs.CL cs.IR cs.LG cs.SI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Real-world knowledge graphs are often characterized by low-frequency
relations - a challenge that has prompted an increasing interest in few-shot
link prediction methods. These methods perform link prediction for a set of new
relations, unseen during training, given only a few example facts of each
relation at test t... | [
{
"created": "Fri, 5 Feb 2021 21:04:31 GMT",
"version": "v1"
}
] | 2021-02-09 | [
[
"Jambor",
"Dora",
""
],
[
"Teru",
"Komal",
""
],
[
"Pineau",
"Joelle",
""
],
[
"Hamilton",
"William L.",
""
]
] |
2102.03444 | Dominik Drees | Dominik Drees, Aaron Scherzinger, Ren\'e H\"agerling, Friedemann
Kiefer, Xiaoyi Jiang | Scalable Robust Graph and Feature Extraction for Arbitrary Vessel
Networks in Large Volumetric Datasets | null | BMC Bioinformatics 22 (2021) 346 | 10.1186/s12859-021-04262-w | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent advances in 3D imaging technologies provide novel insights to
researchers and reveal finer and more detail of examined specimen, especially
in the biomedical domain, but also impose huge challenges regarding scalability
for automated analysis algorithms due to rapidly increasing dataset sizes. In
particular, e... | [
{
"created": "Fri, 5 Feb 2021 23:13:09 GMT",
"version": "v1"
}
] | 2021-06-30 | [
[
"Drees",
"Dominik",
""
],
[
"Scherzinger",
"Aaron",
""
],
[
"Hägerling",
"René",
""
],
[
"Kiefer",
"Friedemann",
""
],
[
"Jiang",
"Xiaoyi",
""
]
] |
2102.03502 | Zhenhan Huang | Zhenhan Huang, Fumihide Tanaka | MSPM: A Modularized and Scalable Multi-Agent Reinforcement
Learning-based System for Financial Portfolio Management | null | PLoS ONE 17(2): e0263689 (2022) | 10.1371/journal.pone.0263689 | null | q-fin.PM cs.AI cs.LG q-fin.CP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Financial portfolio management (PM) is one of the most applicable problems in
reinforcement learning (RL) owing to its sequential decision-making nature.
However, existing RL-based approaches rarely focus on scalability or
reusability to adapt to the ever-changing markets. These approaches are rigid
and unscalable to... | [
{
"created": "Sat, 6 Feb 2021 04:04:57 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Feb 2021 16:19:01 GMT",
"version": "v2"
},
{
"created": "Fri, 11 Jun 2021 08:42:30 GMT",
"version": "v3"
},
{
"created": "Sat, 19 Feb 2022 03:54:41 GMT",
"version": "v4"
}
] | 2022-02-22 | [
[
"Huang",
"Zhenhan",
""
],
[
"Tanaka",
"Fumihide",
""
]
] |
2102.03752 | Yusheng Su | Yusheng Su, Xu Han, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Peng Li,
Jie Zhou, Maosong Sun | CSS-LM: A Contrastive Framework for Semi-supervised Fine-tuning of
Pre-trained Language Models | null | IEEE/ACM Transactions on Audio, Speech, and Language Processing
2021 | 10.1109/TASLP.2021.3105013 | 2329-9290 | cs.CL cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Fine-tuning pre-trained language models (PLMs) has demonstrated its
effectiveness on various downstream NLP tasks recently. However, in many
low-resource scenarios, the conventional fine-tuning strategies cannot
sufficiently capture the important semantic features for downstream tasks. To
address this issue, we intro... | [
{
"created": "Sun, 7 Feb 2021 09:27:26 GMT",
"version": "v1"
},
{
"created": "Mon, 1 Mar 2021 08:50:38 GMT",
"version": "v2"
},
{
"created": "Wed, 3 Mar 2021 11:47:00 GMT",
"version": "v3"
}
] | 2021-11-15 | [
[
"Su",
"Yusheng",
""
],
[
"Han",
"Xu",
""
],
[
"Lin",
"Yankai",
""
],
[
"Zhang",
"Zhengyan",
""
],
[
"Liu",
"Zhiyuan",
""
],
[
"Li",
"Peng",
""
],
[
"Zhou",
"Jie",
""
],
[
"Sun",
"Maosong",
"... |
2102.03814 | Theerawit Wilaiprasitporn | Phairot Autthasan, Rattanaphon Chaisaen, Thapanun Sudhawiyangkul,
Phurin Rangpong, Suktipol Kiatthaveephong, Nat Dilokthanakul, Gun
Bhakdisongkhram, Huy Phan, Cuntai Guan and Theerawit Wilaiprasitporn | MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor
Imagery EEG Classification | null | IEEE Transactions on Biomedical Engineering 2021 | 10.1109/TBME.2021.3137184 | null | eess.SP cs.AI cs.CV cs.LG | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Advances in the motor imagery (MI)-based brain-computer interfaces (BCIs)
allow control of several applications by decoding neurophysiological phenomena,
which are usually recorded by electroencephalography (EEG) using a non-invasive
technique. Despite great advances in MI-based BCI, EEG rhythms are specific to
a sub... | [
{
"created": "Sun, 7 Feb 2021 15:20:23 GMT",
"version": "v1"
},
{
"created": "Sun, 16 May 2021 08:03:59 GMT",
"version": "v2"
},
{
"created": "Thu, 20 May 2021 09:48:47 GMT",
"version": "v3"
},
{
"created": "Fri, 7 Jan 2022 17:20:56 GMT",
"version": "v4"
}
] | 2022-01-10 | [
[
"Autthasan",
"Phairot",
""
],
[
"Chaisaen",
"Rattanaphon",
""
],
[
"Sudhawiyangkul",
"Thapanun",
""
],
[
"Rangpong",
"Phurin",
""
],
[
"Kiatthaveephong",
"Suktipol",
""
],
[
"Dilokthanakul",
"Nat",
""
],
[
"Bhakdis... |
2102.03858 | Zaharah A. Bukhsh | Zaharah A. Bukhsh, Nils Jansen, Aaqib Saeed | Damage detection using in-domain and cross-domain transfer learning | 16 pages, 8 figures, 7 tables | Neural Comput & Applic (2021) | 10.1007/s00521-021-06279-x | null | cs.CV cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We investigate the capabilities of transfer learning in the area of
structural health monitoring. In particular, we are interested in damage
detection for concrete structures. Typical image datasets for such problems are
relatively small, calling for the transfer of learned representation from a
related large-scale d... | [
{
"created": "Sun, 7 Feb 2021 17:36:27 GMT",
"version": "v1"
},
{
"created": "Tue, 5 Oct 2021 09:37:22 GMT",
"version": "v2"
}
] | 2021-10-06 | [
[
"Bukhsh",
"Zaharah A.",
""
],
[
"Jansen",
"Nils",
""
],
[
"Saeed",
"Aaqib",
""
]
] |
2102.03896 | Simon Zhuang | Simon Zhuang, Dylan Hadfield-Menell | Consequences of Misaligned AI | null | NeurIPS 2020 | null | null | cs.AI | http://creativecommons.org/licenses/by/4.0/ | AI systems often rely on two key components: a specified goal or reward
function and an optimization algorithm to compute the optimal behavior for that
goal. This approach is intended to provide value for a principal: the user on
whose behalf the agent acts. The objectives given to these agents often refer
to a parti... | [
{
"created": "Sun, 7 Feb 2021 19:34:04 GMT",
"version": "v1"
}
] | 2021-02-09 | [
[
"Zhuang",
"Simon",
""
],
[
"Hadfield-Menell",
"Dylan",
""
]
] |
2102.03897 | Chetan Srinidhi L | Chetan L. Srinidhi, Seung Wook Kim, Fu-Der Chen, Anne L. Martel | Self-supervised driven consistency training for annotation efficient
histopathology image analysis | null | Medical Image Analysis, Volume 75, January 2022 | 10.1016/j.media.2021.102256 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Training a neural network with a large labeled dataset is still a dominant
paradigm in computational histopathology. However, obtaining such exhaustive
manual annotations is often expensive, laborious, and prone to inter and
Intra-observer variability. While recent self-supervised and semi-supervised
methods can alle... | [
{
"created": "Sun, 7 Feb 2021 19:46:21 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Feb 2021 23:26:44 GMT",
"version": "v2"
},
{
"created": "Sun, 3 Oct 2021 11:07:40 GMT",
"version": "v3"
}
] | 2021-11-03 | [
[
"Srinidhi",
"Chetan L.",
""
],
[
"Kim",
"Seung Wook",
""
],
[
"Chen",
"Fu-Der",
""
],
[
"Martel",
"Anne L.",
""
]
] |
2102.03932 | Fazael Ayatollahi | Fazael Ayatollahi (1 and 2), Shahriar B. Shokouhi (1), Ritse M. Mann
(2), Jonas Teuwen (2 and 3) ((1) Electrical Engineering Department, Iran
University of Science and Technology (IUST), Tehran, Iran, (2) Department of
Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen,
the Netherlands,... | Automatic Breast Lesion Detection in Ultrafast DCE-MRI Using Deep
Learning | null | Medical physics vol. 48,10 (2021): 5897-5907 | 10.1002/mp.15156 | null | eess.IV cs.CV cs.LG | http://creativecommons.org/licenses/by/4.0/ | Purpose: We propose a deep learning-based computer-aided detection (CADe)
method to detect breast lesions in ultrafast DCE-MRI sequences. This method
uses both the three-dimensional spatial information and temporal information
obtained from the early-phase of the dynamic acquisition. Methods: The proposed
CADe method... | [
{
"created": "Sun, 7 Feb 2021 22:03:39 GMT",
"version": "v1"
},
{
"created": "Sun, 15 Aug 2021 19:47:00 GMT",
"version": "v2"
}
] | 2021-11-12 | [
[
"Ayatollahi",
"Fazael",
"",
"1 and 2"
],
[
"Shokouhi",
"Shahriar B.",
"",
"2 and 3"
],
[
"Mann",
"Ritse M.",
"",
"2 and 3"
],
[
"Teuwen",
"Jonas",
"",
"2 and 3"
]
] |
2102.04034 | Andrew Palmer | Andrew W. Palmer, Albi Sema, Wolfram Martens, Peter Rudolph and
Wolfgang Waizenegger | The Autonomous Siemens Tram | 6 pages, presented at the 2020 International Conference on
Intelligent Transportation Systems (ITSC) | A. W. Palmer, A. Sema, W. Martens, P. Rudolph and W. Waizenegger,
"The Autonomous Siemens Tram," 2020 IEEE 23rd ITSC, 2020, pp. 1-6 | 10.1109/ITSC45102.2020.9294699 | null | cs.RO cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper presents the Autonomous Siemens Tram that was publicly
demonstrated in Potsdam, Germany during the InnoTrans 2018 exhibition. The
system was built on a Siemens Combino tram and used a multi-modal sensor suite
to localize the vehicle, and to detect and respond to traffic signals and
obstacles. An overview o... | [
{
"created": "Mon, 8 Feb 2021 07:13:58 GMT",
"version": "v1"
}
] | 2021-02-09 | [
[
"Palmer",
"Andrew W.",
""
],
[
"Sema",
"Albi",
""
],
[
"Martens",
"Wolfram",
""
],
[
"Rudolph",
"Peter",
""
],
[
"Waizenegger",
"Wolfgang",
""
]
] |
2102.04060 | Maxime Ferrera | Maxime Ferrera, Alexandre Eudes, Julien Moras, Martial Sanfourche, Guy
Le Besnerais | OV$^{2}$SLAM : A Fully Online and Versatile Visual SLAM for Real-Time
Applications | Accepted for publication in IEEE Robotics and Automation Letters
(RA-L). Code is available at : \url{https://github.com/ov2slam/ov2slam} | IEEE Robotics and Automation Letters, IEEE 2021 | null | null | cs.CV cs.RO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Many applications of Visual SLAM, such as augmented reality, virtual reality,
robotics or autonomous driving, require versatile, robust and precise
solutions, most often with real-time capability. In this work, we describe
OV$^{2}$SLAM, a fully online algorithm, handling both monocular and stereo
camera setups, vario... | [
{
"created": "Mon, 8 Feb 2021 08:39:23 GMT",
"version": "v1"
}
] | 2021-02-09 | [
[
"Ferrera",
"Maxime",
""
],
[
"Eudes",
"Alexandre",
""
],
[
"Moras",
"Julien",
""
],
[
"Sanfourche",
"Martial",
""
],
[
"Besnerais",
"Guy Le",
""
]
] |
2102.04201 | Jennifer Cobbe Dr | Jennifer Cobbe, Michelle Seng Ah Lee, Jatinder Singh | Reviewable Automated Decision-Making: A Framework for Accountable
Algorithmic Systems | null | ACM Conference on Fairness, Accountability, and Transparency
(FAccT 21), March 2021, Virtual Event, Canada | null | null | cs.CY cs.AI | http://creativecommons.org/licenses/by/4.0/ | This paper introduces reviewability as a framework for improving the
accountability of automated and algorithmic decision-making (ADM) involving
machine learning. We draw on an understanding of ADM as a socio-technical
process involving both human and technical elements, beginning before a
decision is made and extend... | [
{
"created": "Tue, 26 Jan 2021 18:15:34 GMT",
"version": "v1"
},
{
"created": "Wed, 10 Feb 2021 11:48:42 GMT",
"version": "v2"
}
] | 2021-02-11 | [
[
"Cobbe",
"Jennifer",
""
],
[
"Lee",
"Michelle Seng Ah",
""
],
[
"Singh",
"Jatinder",
""
]
] |
2102.04202 | Shoffan Saifullah | Shoffan Saifullah | Segmentasi Citra Menggunakan Metode Watershed Transform Berdasarkan
Image Enhancement Dalam Mendeteksi Embrio Telur | 8 pages, in Indonesian language, 6 figures | Systemic: Information System and Informatics Journal, 5(2),
(2019), 53-60 | 10.29080/systemic.v5i2.798 | null | eess.IV cs.CV | http://creativecommons.org/licenses/by/4.0/ | Image processing can be applied in the detection of egg embryos. The egg
embryos detection is processed using a segmentation process. The segmentation
divides the image according to the area that is divided. This process requires
improvement of the image that is processed to obtain optimal results. This
study will an... | [
{
"created": "Mon, 8 Feb 2021 14:03:51 GMT",
"version": "v1"
}
] | 2021-02-14 | [
[
"Saifullah",
"Shoffan",
""
]
] |
2102.04216 | Anusha Bompelli | Anusha Bompelli, Yanshan Wang, Ruyuan Wan, Esha Singh, Yuqi Zhou, Lin
Xu, David Oniani, Bhavani Singh Agnikula Kshatriya, Joyce (Joy) E.
Balls-Berry, and Rui Zhang | Social and behavioral determinants of health in the era of artificial
intelligence with electronic health records: A scoping review | 32 pages, 5 figures | Health Data Science. 2021 Aug 24;2021:9759016 | 10.34133/2021/9759016 | Article ID 9759016 | cs.CY cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Background: There is growing evidence that social and behavioral determinants
of health (SBDH) play a substantial effect in a wide range of health outcomes.
Electronic health records (EHRs) have been widely employed to conduct
observational studies in the age of artificial intelligence (AI). However,
there has been l... | [
{
"created": "Fri, 22 Jan 2021 09:03:39 GMT",
"version": "v1"
},
{
"created": "Sun, 13 Jun 2021 17:50:11 GMT",
"version": "v2"
}
] | 2021-10-12 | [
[
"Bompelli",
"Anusha",
"",
"Joy"
],
[
"Wang",
"Yanshan",
"",
"Joy"
],
[
"Wan",
"Ruyuan",
"",
"Joy"
],
[
"Singh",
"Esha",
"",
"Joy"
],
[
"Zhou",
"Yuqi",
"",
"Joy"
],
[
"Xu",
"Lin",
"",
"Joy"
],
[
... |
2102.04341 | Jonathan Kelly | Justin Tomasi, Brandon Wagstaff, Steven L. Waslander, Jonathan Kelly | Learned Camera Gain and Exposure Control for Improved Visual Feature
Detection and Matching | In IEEE Robotics and Automation Letters (RA-L) and presented at the
IEEE International Conference on Robotics and Automation (ICRA'21), Xi'an,
China, May 30-Jun. 5, 2021 | IEEE Robotics and Automation Letters (RA-L), Vol. 6, No. 2, pp.
2028-2035, Apr. 2021 | 10.1109/LRA.2021.3058909 | null | cs.RO cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Successful visual navigation depends upon capturing images that contain
sufficient useful information. In this letter, we explore a data-driven
approach to account for environmental lighting changes, improving the quality
of images for use in visual odometry (VO) or visual simultaneous localization
and mapping (SLAM)... | [
{
"created": "Mon, 8 Feb 2021 16:46:09 GMT",
"version": "v1"
},
{
"created": "Sun, 28 Feb 2021 17:52:10 GMT",
"version": "v2"
},
{
"created": "Mon, 11 Jul 2022 05:00:57 GMT",
"version": "v3"
}
] | 2022-07-12 | [
[
"Tomasi",
"Justin",
""
],
[
"Wagstaff",
"Brandon",
""
],
[
"Waslander",
"Steven L.",
""
],
[
"Kelly",
"Jonathan",
""
]
] |
2102.04366 | Lucas Prado Osco | Mauro dos Santos de Arruda, Lucas Prado Osco, Plabiany Rodrigo Acosta,
Diogo Nunes Gon\c{c}alves, Jos\'e Marcato Junior, Ana Paula Marques Ramos,
Edson Takashi Matsubara, Zhipeng Luo, Jonathan Li, Jonathan de Andrade Silva,
Wesley Nunes Gon\c{c}alves | Counting and Locating High-Density Objects Using Convolutional Neural
Network | 15 pages, 10 figures, 8 tables | Expert Systems with Applications, 2022 | 10.1016/j.eswa.2022.116555 | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | This paper presents a Convolutional Neural Network (CNN) approach for
counting and locating objects in high-density imagery. To the best of our
knowledge, this is the first object counting and locating method based on a
feature map enhancement and a Multi-Stage Refinement of the confidence map. The
proposed method wa... | [
{
"created": "Mon, 8 Feb 2021 17:17:10 GMT",
"version": "v1"
}
] | 2022-05-31 | [
[
"de Arruda",
"Mauro dos Santos",
""
],
[
"Osco",
"Lucas Prado",
""
],
[
"Acosta",
"Plabiany Rodrigo",
""
],
[
"Gonçalves",
"Diogo Nunes",
""
],
[
"Junior",
"José Marcato",
""
],
[
"Ramos",
"Ana Paula Marques",
""
],
[
... |
2102.04394 | Fabio Gonzalez | Fabio A. Gonz\'alez, Alejandro Gallego, Santiago Toledo-Cort\'es,
Vladimir Vargas-Calder\'on | Learning with Density Matrices and Random Features | Final version published in Quantum Mach. Intell. 4, 23 (2022) | Quantum Mach. Intell. 4, 23 (2022) | 10.1007/s42484-022-00079-9 | null | cs.LG cs.AI quant-ph | http://creativecommons.org/licenses/by-sa/4.0/ | A density matrix describes the statistical state of a quantum system. It is a
powerful formalism to represent both the quantum and classical uncertainty of
quantum systems and to express different statistical operations such as
measurement, system combination and expectations as linear algebra operations.
This paper ... | [
{
"created": "Mon, 8 Feb 2021 17:54:59 GMT",
"version": "v1"
},
{
"created": "Fri, 12 Feb 2021 14:40:04 GMT",
"version": "v2"
},
{
"created": "Tue, 21 Sep 2021 01:40:47 GMT",
"version": "v3"
},
{
"created": "Tue, 9 Nov 2021 04:05:52 GMT",
"version": "v4"
},
{
"cre... | 2024-05-01 | [
[
"González",
"Fabio A.",
""
],
[
"Gallego",
"Alejandro",
""
],
[
"Toledo-Cortés",
"Santiago",
""
],
[
"Vargas-Calderón",
"Vladimir",
""
]
] |
2102.04402 | Xueguang Lyu | Xueguang Lyu, Yuchen Xiao, Brett Daley, Christopher Amato | Contrasting Centralized and Decentralized Critics in Multi-Agent
Reinforcement Learning | null | Proceedings of the 20th International Conference on Autonomous
Agents and MultiAgent Systems (AAMAS). 2021 | null | null | cs.LG cs.AI | http://creativecommons.org/licenses/by-sa/4.0/ | Centralized Training for Decentralized Execution, where agents are trained
offline using centralized information but execute in a decentralized manner
online, has gained popularity in the multi-agent reinforcement learning
community. In particular, actor-critic methods with a centralized critic and
decentralized acto... | [
{
"created": "Mon, 8 Feb 2021 18:08:11 GMT",
"version": "v1"
},
{
"created": "Thu, 2 Dec 2021 21:33:13 GMT",
"version": "v2"
}
] | 2021-12-06 | [
[
"Lyu",
"Xueguang",
""
],
[
"Xiao",
"Yuchen",
""
],
[
"Daley",
"Brett",
""
],
[
"Amato",
"Christopher",
""
]
] |
2102.04566 | Lucas Prado Osco | Patrik Ol\~a Bressan, Jos\'e Marcato Junior, Jos\'e Augusto Correa
Martins, Diogo Nunes Gon\c{c}alves, Daniel Matte Freitas, Lucas Prado Osco,
Jonathan de Andrade Silva, Zhipeng Luo, Jonathan Li, Raymundo Cordero Garcia,
Wesley Nunes Gon\c{c}alves | Semantic Segmentation with Labeling Uncertainty and Class Imbalance | 15 pages, 9 figures, 3 tables | International Journal of Applied Earth Observation and
Geoinformation, 2022 | 10.1016/j.jag.2022.102690 | null | cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Recently, methods based on Convolutional Neural Networks (CNN) achieved
impressive success in semantic segmentation tasks. However, challenges such as
the class imbalance and the uncertainty in the pixel-labeling process are not
completely addressed. As such, we present a new approach that calculates a
weight for eac... | [
{
"created": "Mon, 8 Feb 2021 22:53:33 GMT",
"version": "v1"
}
] | 2022-05-31 | [
[
"Bressan",
"Patrik Olã",
""
],
[
"Junior",
"José Marcato",
""
],
[
"Martins",
"José Augusto Correa",
""
],
[
"Gonçalves",
"Diogo Nunes",
""
],
[
"Freitas",
"Daniel Matte",
""
],
[
"Osco",
"Lucas Prado",
""
],
[
"Si... |
2102.04652 | Xiangzeng Zhou | Xiangzeng Zhou and Pan Pan and Yun Zheng and Yinghui Xu and Rong Jin | Large Scale Long-tailed Product Recognition System at Alibaba | Acccepted by CIKM 2020 | In Proceedings of the 29th ACM International Conference on
Information and Knowledge Management (CIKM20), 3353-3356 (2020) | 10.1145/3340531.3417445 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A practical large scale product recognition system suffers from the
phenomenon of long-tailed imbalanced training data under the E-commercial
circumstance at Alibaba. Besides product images at Alibaba, plenty of image
related side information (e.g. title, tags) reveal rich semantic information
about images. Prior wor... | [
{
"created": "Tue, 9 Feb 2021 05:34:30 GMT",
"version": "v1"
}
] | 2021-02-10 | [
[
"Zhou",
"Xiangzeng",
""
],
[
"Pan",
"Pan",
""
],
[
"Zheng",
"Yun",
""
],
[
"Xu",
"Yinghui",
""
],
[
"Jin",
"Rong",
""
]
] |
2102.04667 | Yanhao Zhang | Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Jianmin Wu, Yinghui Xu,
Rong Jin | Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting
Richness of User Click Behavior for Visual Search Relevance | accepted by CIKM 2019 | CIKM 2019: 2489-2497 | 10.1145/3357384.3357800 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Visual search plays an essential role for E-commerce. To meet the search
demands of users and promote shopping experience at Alibaba, visual search
relevance of real-shot images is becoming the bottleneck. Traditional visual
search paradigm is usually based upon supervised learning with labeled data.
However, large-s... | [
{
"created": "Tue, 9 Feb 2021 06:31:20 GMT",
"version": "v1"
}
] | 2021-02-10 | [
[
"Zhang",
"Yanhao",
""
],
[
"Pan",
"Pan",
""
],
[
"Zheng",
"Yun",
""
],
[
"Zhao",
"Kang",
""
],
[
"Wu",
"Jianmin",
""
],
[
"Xu",
"Yinghui",
""
],
[
"Jin",
"Rong",
""
]
] |
2102.04674 | Yanhao Zhang | Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Yingya Zhang, Xiaofeng
Ren, Rong Jin | Visual Search at Alibaba | accepted by KDD 2018 | KDD 2018: 993-1001 | 10.1145/3219819.3219820 | null | cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper introduces the large scale visual search algorithm and system
infrastructure at Alibaba. The following challenges are discussed under the
E-commercial circumstance at Alibaba (a) how to handle heterogeneous image data
and bridge the gap between real-shot images from user query and the online
images. (b) ho... | [
{
"created": "Tue, 9 Feb 2021 06:46:50 GMT",
"version": "v1"
}
] | 2021-02-10 | [
[
"Zhang",
"Yanhao",
""
],
[
"Pan",
"Pan",
""
],
[
"Zheng",
"Yun",
""
],
[
"Zhao",
"Kang",
""
],
[
"Zhang",
"Yingya",
""
],
[
"Ren",
"Xiaofeng",
""
],
[
"Jin",
"Rong",
""
]
] |
2102.04780 | Sutharsan Mahendren Mr | Sutharsan Mahendren, Chamira Edussooriya, Ranga Rodrigo | Diverse Single Image Generation with Controllable Global Structure | Published in the Neurocomputing Journal | Neurocomputing 528(2023)97-112 | 10.1016/j.neucom.2023.01.011 | null | cs.CV eess.IV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Image generation from a single image using generative adversarial networks is
quite interesting due to the realism of generated images. However, recent
approaches need improvement for such realistic and diverse image generation,
when the global context of the image is important such as in face, animal, and
architectu... | [
{
"created": "Tue, 9 Feb 2021 11:52:48 GMT",
"version": "v1"
},
{
"created": "Mon, 15 Feb 2021 05:22:34 GMT",
"version": "v2"
},
{
"created": "Thu, 20 Jan 2022 05:25:10 GMT",
"version": "v3"
},
{
"created": "Wed, 25 Jan 2023 13:10:39 GMT",
"version": "v4"
}
] | 2023-01-26 | [
[
"Mahendren",
"Sutharsan",
""
],
[
"Edussooriya",
"Chamira",
""
],
[
"Rodrigo",
"Ranga",
""
]
] |
2102.04816 | Abdelrahman Abdallah | Daniyar Nurseitov, Kairat Bostanbekov, Maksat Kanatov, Anel Alimova,
Abdelrahman Abdallah, Galymzhan Abdimanap | Classification of Handwritten Names of Cities and Handwritten Text
Recognition using Various Deep Learning Models | null | Advances in Science, Technology and Engineering Systems. 5,
934-943 (2020) | 10.25046/aj0505114 | null | cs.CV | http://creativecommons.org/licenses/by/4.0/ | This article discusses the problem of handwriting recognition in Kazakh and
Russian languages. This area is poorly studied since in the literature there
are almost no works in this direction. We have tried to describe various
approaches and achievements of recent years in the development of handwritten
recognition mo... | [
{
"created": "Tue, 9 Feb 2021 13:34:16 GMT",
"version": "v1"
}
] | 2021-02-10 | [
[
"Nurseitov",
"Daniyar",
""
],
[
"Bostanbekov",
"Kairat",
""
],
[
"Kanatov",
"Maksat",
""
],
[
"Alimova",
"Anel",
""
],
[
"Abdallah",
"Abdelrahman",
""
],
[
"Abdimanap",
"Galymzhan",
""
]
] |
2102.04916 | Pierre Aumjaud | Pierre Aumjaud, David McAuliffe, Francisco Javier Rodr\'iguez Lera,
Philip Cardiff | rl_reach: Reproducible Reinforcement Learning Experiments for Robotic
Reaching Tasks | 7 pages, 5 figures | Software Impacts. 8 (2021) 100061 | 10.1016/j.simpa.2021.100061 | null | cs.LG cs.AI cs.RO | http://creativecommons.org/licenses/by-sa/4.0/ | Training reinforcement learning agents at solving a given task is highly
dependent on identifying optimal sets of hyperparameters and selecting suitable
environment input / output configurations. This tedious process could be eased
with a straightforward toolbox allowing its user to quickly compare different
training... | [
{
"created": "Tue, 9 Feb 2021 16:14:10 GMT",
"version": "v1"
},
{
"created": "Mon, 1 Mar 2021 19:32:01 GMT",
"version": "v2"
}
] | 2021-03-03 | [
[
"Aumjaud",
"Pierre",
""
],
[
"McAuliffe",
"David",
""
],
[
"Lera",
"Francisco Javier Rodríguez",
""
],
[
"Cardiff",
"Philip",
""
]
] |
2102.04993 | Marc G\'orriz Blanch | Marc G\'orriz, Saverio Blasi, Alan F. Smeaton, Noel E. O'Connor, Marta
Mrak | Attention-Based Neural Networks for Chroma Intra Prediction in Video
Coding | null | IEEE Journal of Selected Topics in Signal Processing, 2020 | 10.1109/JSTSP.2020.3044482 | null | eess.IV cs.CC cs.CV cs.LG cs.MM | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Neural networks can be successfully used to improve several modules of
advanced video coding schemes. In particular, compression of colour components
was shown to greatly benefit from usage of machine learning models, thanks to
the design of appropriate attention-based architectures that allow the
prediction to explo... | [
{
"created": "Tue, 9 Feb 2021 18:01:22 GMT",
"version": "v1"
}
] | 2021-02-10 | [
[
"Górriz",
"Marc",
""
],
[
"Blasi",
"Saverio",
""
],
[
"Smeaton",
"Alan F.",
""
],
[
"O'Connor",
"Noel E.",
""
],
[
"Mrak",
"Marta",
""
]
] |
2102.05067 | Silvia Cascianelli PhD | Silvia Cascianelli, Gabriele Costante, Alessandro Devo, Thomas A.
Ciarfuglia, Paolo Valigi, Mario L. Fravolini | The Role of the Input in Natural Language Video Description | In IEEE Transactions on Multimedia | IEEE Transactions on Multimedia, 22(1), 271-283 (2019) | null | null | cs.CV cs.CL cs.MM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Natural Language Video Description (NLVD) has recently received strong
interest in the Computer Vision, Natural Language Processing (NLP), Multimedia,
and Autonomous Robotics communities. The State-of-the-Art (SotA) approaches
obtained remarkable results when tested on the benchmark datasets. However,
those approache... | [
{
"created": "Tue, 9 Feb 2021 19:00:35 GMT",
"version": "v1"
}
] | 2021-02-11 | [
[
"Cascianelli",
"Silvia",
""
],
[
"Costante",
"Gabriele",
""
],
[
"Devo",
"Alessandro",
""
],
[
"Ciarfuglia",
"Thomas A.",
""
],
[
"Valigi",
"Paolo",
""
],
[
"Fravolini",
"Mario L.",
""
]
] |
2102.05126 | Jon\'a\v{s} Kulh\'anek | Jon\'a\v{s} Kulh\'anek and Vojt\v{e}ch Hude\v{c}ek and Tom\'a\v{s}
Nekvinda and Ond\v{r}ej Du\v{s}ek | AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue
with Pre-Trained Language Models | null | Proceedings of the 3rd Workshop on Natural Language Processing for
Conversational AI (2021), 198-210 | 10.18653/v1/2021.nlp4convai-1.19 | null | cs.CL cs.AI cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Attention-based pre-trained language models such as GPT-2 brought
considerable progress to end-to-end dialogue modelling. However, they also
present considerable risks for task-oriented dialogue, such as lack of
knowledge grounding or diversity. To address these issues, we introduce
modified training objectives for l... | [
{
"created": "Tue, 9 Feb 2021 20:53:34 GMT",
"version": "v1"
},
{
"created": "Mon, 27 Sep 2021 08:28:40 GMT",
"version": "v2"
},
{
"created": "Fri, 14 Jan 2022 14:42:11 GMT",
"version": "v3"
}
] | 2022-01-17 | [
[
"Kulhánek",
"Jonáš",
""
],
[
"Hudeček",
"Vojtěch",
""
],
[
"Nekvinda",
"Tomáš",
""
],
[
"Dušek",
"Ondřej",
""
]
] |
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