text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
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present a including proposed. modeling paper, In cross-layer the is power assessment framework | In the present paper, a cross-layer assessment framework including power modeling is proposed. | 36,700 |
and cross-layer energy a improves significantly throughput. that efficiency We demonstrate approach overall | We demonstrate that a cross-layer approach significantly improves energy efficiency and overall throughput. | 36,701 |
LPWAN assessment been open-source First, an framework conceived. has | First, an open-source LPWAN assessment framework has been conceived. | 36,702 |
hypotheses schemes. allows evaluating and and It testing | It allows testing and evaluating hypotheses and schemes. | 36,703 |
Secondly, is assessed. protocol representative a LoRaWAN as case, the | Secondly, as a representative case, the LoRaWAN protocol is assessed. | 36,704 |
point-optimal reference our test For efficient. and a is correctly density, nearly specified | For a correctly specified reference density, our test is point-optimal and nearly efficient. | 36,705 |
inpainting frames. of We for recovering video missing regions video data-driven a new present method | We present a new data-driven video inpainting method for recovering missing regions of video frames. | 36,706 |
in Our end-to-end jointly trains an manner. sub-networks both method | Our method jointly trains both sub-networks in an end-to-end manner. | 36,707 |
their uncertainty, errors may lead rarely these which However, methods to quantify downstream in analysis. | However, these methods rarely quantify their uncertainty, which may lead to errors in downstream analysis. | 36,708 |
Additionally, replaced iterative is parallel, one. standard the by a multi-threaded implementation | Additionally, the standard iterative implementation is replaced by a parallel, multi-threaded one. | 36,709 |
describe We details scalability strong scaling and formulation. using the a its implementation analyze | We describe the implementation details and analyze its scalability using a strong scaling formulation. | 36,710 |
as training process. sequence a stochastic We the model | We model the training sequence as a stochastic process. | 36,711 |
models evidence We argue are empirical power-law processes. that natural from suitable for | We argue from empirical evidence that power-law models are suitable for natural processes. | 36,712 |
like Random where lunch is transfer typing work. no-free does model not learning | Random typing model is like no-free lunch where transfer learning does not work. | 36,713 |
samples independently the distribution. Zeta programs zeta process from | Zeta process independently samples programs from the zeta distribution. | 36,714 |
database of a genetics model A by sub-programs of uses inspired common sub-programs. | A model of common sub-programs inspired by genetics uses a database of sub-programs. | 36,715 |
An samples Zeta distribution. process evolutionary from mutations zeta | An evolutionary zeta process samples mutations from Zeta distribution. | 36,716 |
semi-intrusive family uncertainty for of introduced. models (UP) multiscale propagation methods A is | A family of semi-intrusive uncertainty propagation (UP) methods for multiscale models is introduced. | 36,717 |
tested have case on These algorithms based dynamics. been semi-intrusive studies two on reaction-diffusion | These semi-intrusive algorithms have been tested on two case studies based on reaction-diffusion dynamics. | 36,718 |
are important human-machine learning for electromyography Machine control. surface device and classifiers interfacing using | Machine learning classifiers using surface electromyography are important for human-machine interfacing and device control. | 36,719 |
features extracted (SVMs) vector classifiers as machines manually based Conventional use such on support e.g. | Conventional classifiers such as support vector machines (SVMs) use manually extracted features based on e.g. | 36,720 |
advantage. - networks, can automatically extract an Deep important contrast, features neural specific person by | Deep neural networks, by contrast, can automatically extract person specific features - an important advantage. | 36,721 |
have images. images Retinal among the medical resolution highest clarity and | Retinal images have the highest resolution and clarity among medical images. | 36,722 |
Experimental state-of-the-art demonstrate evaluations methods. network that outperforms proposed current the | Experimental evaluations demonstrate that the proposed network outperforms current state-of-the-art methods. | 36,723 |
important performance that Ablative improvement. analysis the SSA in is factor shows an indeed | Ablative analysis shows that the SSA is indeed an important factor in performance improvement. | 36,724 |
resulting array non-uniform is The sparse. highly linear | The resulting non-uniform linear array is highly sparse. | 36,725 |
patterns sparse the Also, arrays. than better lobe other exhibits side SCA | Also, the SCA exhibits better side lobe patterns than other sparse arrays. | 36,726 |
advance concern face privacy recognition leakage. The people's techniques the regarding new of also arises | The advance of new face recognition techniques also arises people's concern regarding the privacy leakage. | 36,727 |
in protection, terms privacy preservation, evaluate utility similarity. and structure the approach proposed We of | We evaluate the proposed approach in terms of privacy protection, utility preservation, and structure similarity. | 36,728 |
is accurate with of steatosis An pathology importance. tissue clinical quantification samples high | An accurate steatosis quantification with pathology tissue samples is of high clinical importance. | 36,729 |
introduces learning control. generative new deep This synthesis for and motion paper network human a | This paper introduces a new generative deep learning network for human motion synthesis and control. | 36,730 |
describe method motion We first for data. prerecorded training efficient a an from model RNNs | We first describe an efficient method for training a RNNs model from prerecorded motion data. | 36,731 |
our We models. model against baseline the by comparison generative show superiority of | We show the superiority of our generative model by comparison against baseline models. | 36,732 |
many areas is Deep learning ubiquitous areas across computer of vision. | Deep learning is ubiquitous across many areas areas of computer vision. | 36,733 |
large It for scale scale often datasets fine-tuned on before being small-to-medium problems. requires training | It often requires large scale datasets for training before being fine-tuned on small-to-medium scale problems. | 36,734 |
datasets. in classes paper between we specifically, overlapping the this utilize More | More specifically, in this paper we utilize the overlapping classes between datasets. | 36,735 |
available state-of-the-art We three results demonstrate benchmarks. publicly on | We demonstrate state-of-the-art results on three publicly available benchmarks. | 36,736 |
run have CNNs segmentation for time Deep requirements. memory and high semantic | Deep CNNs for semantic segmentation have high memory and run time requirements. | 36,737 |
to shuffled, grouped, proposed efficient like Various approaches make CNNs convolutions. depth-wise separable have been | Various approaches have been proposed to make CNNs efficient like grouped, shuffled, depth-wise separable convolutions. | 36,738 |
cases model AMD normal is minimal using on and mixture a trained of data. This | This model is trained on a mixture of normal and AMD cases using minimal data. | 36,739 |
with methods. par Our model's also existing is performance on the | Our model's performance is also on par with the existing methods. | 36,740 |
C-arm for solution Augmented marker-free proposes Reality "technician-in-the-loop" (AR) repositioning. work This a | This work proposes a marker-free "technician-in-the-loop" Augmented Reality (AR) solution for C-arm repositioning. | 36,741 |
We in simulating experiments setting trauma a orthopedic surgery. conduct | We conduct experiments in a setting simulating orthopedic trauma surgery. | 36,742 |
are relays (AF) and forward Amplifyand- often decode-and-forward used. (DF) | Amplifyand- forward (AF) and decode-and-forward (DF) relays are often used. | 36,743 |
as Hybrid system this to We refer approach. the | We refer to this system as the Hybrid approach. | 36,744 |
to Carlo are validate simulations analytical results. throughout the this used paper Monte | Monte Carlo simulations are used throughout this paper to validate the analytical results. | 36,745 |
parameters this investigated is system in several of paper. The impact | The impact of several system parameters is investigated in this paper. | 36,746 |
the model ARM. Re-identification as We to proposed Metalearning refer Attention-based | We refer to the proposed Attention-based Re-identification Metalearning model as ARM. | 36,747 |
As be accurate. such, RECIST must annotations | As such, RECIST annotations must be accurate. | 36,748 |
region method RECIST proposed stages: consists normalization of two The and estimation. lesion | The proposed method consists of two stages: lesion region normalization and RECIST estimation. | 36,749 |
learned and an in fashion. SHN both end-to-end be can STN | STN and SHN can both be learned in an end-to-end fashion. | 36,750 |
core applications. various in of tasks counting the is Crowd one surveillance | Crowd counting is one of the core tasks in various surveillance applications. | 36,751 |
present problems. we both address this unified to work, In solution a | In this work, we present a unified solution to address both problems. | 36,752 |
accurate method signatures. verifying This online paper for presents an | This paper presents an accurate method for verifying online signatures. | 36,753 |
a one-class modeled using are and signatures user's classifier. Finally, classified | Finally, user's signatures are modeled and classified using a one-class classifier. | 36,754 |
independent datasets proposed thanks on method signature The is self-taught learning. to | The proposed method is independent on signature datasets thanks to self-taught learning. | 36,755 |
hinders to rapid research reproduce prototyping hurdles results. researchers and This from poses | This hinders researchers from rapid prototyping and poses hurdles to reproduce research results. | 36,756 |
The paper this draft AIRLab and with analyses. of first presented performance snippets outlines code | The presented draft of this paper outlines AIRLab with first code snippets and performance analyses. | 36,757 |
more a exhaustive follow soon. introduction final A as version will | A more exhaustive introduction will follow as a final version soon. | 36,758 |
e.g. Failure learning, cases black-box deep of | Failure cases of black-box deep learning, e.g. | 36,759 |
might have adversarial severe in healthcare. consequences examples, | adversarial examples, might have severe consequences in healthcare. | 36,760 |
studied mostly the Yet calibrated attacks. real-world images of are in such failures with context | Yet such failures are mostly studied in the context of real-world images with calibrated attacks. | 36,761 |
studies the demystify To adversarial examples, to need be designed. rigorous | To demystify the adversarial examples, rigorous studies need to be designed. | 36,762 |
images. medical hinders such the study Unfortunately, complexity images directly of medical the design from | Unfortunately, complexity of the medical images hinders such study design directly from the medical images. | 36,763 |
domain-independent task planning. encoding present for a We general constraint-based | We present a general constraint-based encoding for domain-independent task planning. | 36,764 |
effects optional as expressed causal Task conditions planning and by is relationships of actions. characterized | Task planning is characterized by causal relationships expressed as conditions and effects of optional actions. | 36,765 |
It time-oriented scheduling. work of in in the spirit a constraint-based follows previous view | It follows a time-oriented view in the spirit of previous work in constraint-based scheduling. | 36,766 |
need accurate segmentation. skin This for lesion and underlines automatic for approach an the | This underlines the need for an accurate and automatic approach for skin lesion segmentation. | 36,767 |
neural tackle network To SkinNet. issue, called (CNN) we a convolutional this propose | To tackle this issue, we propose a convolutional neural network (CNN) called SkinNet. | 36,768 |
is a of proposed CNN U-Net. The version modified | The proposed CNN is a modified version of U-Net. | 36,769 |
strategies. injection of mode normalization that method collapse to we leads because the found However, | However, we found that the injection method leads to mode collapse because of normalization strategies. | 36,770 |
biasing propose latent the information. on central to the normalization we inject criteria, code Based | Based on the criteria, we propose central biasing normalization to inject the latent code information. | 36,771 |
expensive dietary prone methods errors. conventional are time-consuming, and The assessment to | The conventional dietary assessment methods are time-consuming, expensive and prone to errors. | 36,772 |
with and existing are over FOND empirically planners new planners existing compared The benchmarks. resulting | The resulting FOND planners are compared empirically with existing planners over existing and new benchmarks. | 36,773 |
scenarios. industrial vehicle are Connected deployed fleets worldwide IoT in several | Connected vehicle fleets are deployed worldwide in several industrial IoT scenarios. | 36,774 |
highlighted experimental proposed results. the The through several superiority is method of | The superiority of the proposed method is highlighted through several experimental results. | 36,775 |
current Unfortunately, in problem benchmarks task and limited for diversity. are this size | Unfortunately, current benchmarks for this problem are limited in size and task diversity. | 36,776 |
on novel based a paper proposes This image multi-exposure fusion exposure method compensation. | This paper proposes a novel multi-exposure image fusion method based on exposure compensation. | 36,777 |
one fusion multi-exposure The image combined images are of compensated existing finally by methods. | The compensated images are finally combined by one of existing multi-exposure image fusion methods. | 36,778 |
building Games playing a (CCGs). is in Deck Collectible component crucial Card | Deck building is a crucial component in playing Collectible Card Games (CCGs). | 36,779 |
multimodal brings demonstrate information notable Practical framework using our incorporating that benefits. experiments | Practical experiments demonstrate that incorporating multimodal information using our framework brings notable benefits. | 36,780 |
is a thousand picture words. A worth | A picture is worth a thousand words. | 36,781 |
information exhibit contrasts and associated with the thus same anatomy capture similarities. These underlying | These contrasts capture information associated with the same underlying anatomy and thus exhibit similarities. | 36,782 |
a contrasts. dictionaries The stage multiple correlations capture that learns first of among group | The first stage learns a group of dictionaries that capture correlations among multiple contrasts. | 36,783 |
representative band extracts the and each as takes a globally It whole most bands. | It takes each band as a whole and globally extracts the most representative bands. | 36,784 |
diverse. However, homogeneous whose features spectral regions to are different objects, different correspond | However, different homogeneous regions correspond to different objects, whose spectral features are diverse. | 36,785 |
main classical PCA In four to models, has contrast properties. SuperPCA | In contrast to classical PCA models, SuperPCA has four main properties. | 36,786 |
to classification leading resistant, discriminative, performance. are and The features improved resulting compact, HSI noise | The resulting features are discriminative, compact, and noise resistant, leading to improved HSI classification performance. | 36,787 |
systems. self-reproducing studying generation tool P. theory for Kabamba a as developed | P. Kabamba developed generation theory as a tool for studying self-reproducing systems. | 36,788 |
a exhibit theory. and also illustrating fixed-point self-replication connection between examples We | We also exhibit examples illustrating a connection between self-replication and fixed-point theory. | 36,789 |
systems is comparison's OFDM presented For of conventional paper. the also performance the throughout sake, | For comparison's sake, the performance of conventional OFDM systems is also presented throughout the paper. | 36,790 |
results. and validates This complements currently available | This complements and validates currently available results. | 36,791 |
supervises accurate motion, manner. that a in but learning sparse structure from | structure from motion, that supervises learning in a sparse but accurate manner. | 36,792 |
for The code publicly is available. the method proposed | The code for the proposed method is publicly available. | 36,793 |
the data However, certain a when (i.e. body position from labeled | However, when the labeled data from a certain body position (i.e. | 36,794 |
missing, how (i.e. domain) positions from to the target is data other leverage | target domain) is missing, how to leverage the data from other positions (i.e. | 36,795 |
of this labels domain) to position? the help activity source learn | source domain) to help learn the activity labels of this position? | 36,796 |
selected domain, transfer source accurate With between perform domains. we knowledge need to the | With the selected source domain, we need to perform accurate knowledge transfer between domains. | 36,797 |
property. learn between distance only the global ignoring the domains Existing local methods while | Existing methods only learn the global distance between domains while ignoring the local property. | 36,798 |
property the based \textit{Stratified} local domains. our of on is capture distance to STL proposed | STL is based on our proposed \textit{Stratified} distance to capture the local property of domains. | 36,799 |
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