text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
We benchmark performance state-of-the-art datasets. in achieve extensive | We achieve state-of-the-art performance in extensive benchmark datasets. | 39,000 |
iris recognition. of paper post-mortem This analysis presents unique a human | This paper presents a unique analysis of post-mortem human iris recognition. | 39,001 |
tracking a In using a optimally we as approach. practice, path problem solve K-shortest this | In practice, we solve this optimally as a tracking problem using a K-shortest path approach. | 39,002 |
these are of relation Insightful all conclusions to aspects. offered three in | Insightful conclusions are offered in relation to all three of these aspects. | 39,003 |
Thus, has size departments. railway from increasing EMU associated fleet the attention attracted prediction of | Thus, the prediction of EMU fleet size has attracted increasing attention from associated railway departments. | 39,004 |
in two networks analyzed differences of computation The and performances are these experiments in-depth. | The differences and performances of these two networks in computation experiments are analyzed in-depth. | 39,005 |
of is object nearby an among symmetries and among Distinction poses challenging. | Distinction among nearby poses and among symmetries of an object is challenging. | 39,006 |
In we group-theoretic both. a propose unified, this to paper, approach tackle | In this paper, we propose a unified, group-theoretic approach to tackle both. | 39,007 |
to We matrices. sample Metropolis-Hastings from algorithm space propose the correlation of uniformly a novel | We propose a novel Metropolis-Hastings algorithm to sample uniformly from the space of correlation matrices. | 39,008 |
no from However or other populations. population fully animal human human is isolated | However no human population is fully isolated from other human or animal populations. | 39,009 |
neural improvements deep object by to have Driven pose brought networks, methods recent estimation. significant | Driven by deep neural networks, recent methods have brought significant improvements to object pose estimation. | 39,010 |
the have approach. encourage research, To we reproducible proposed for released codes our | To encourage reproducible research, we have released the codes for our proposed approach. | 39,011 |
features. Convolutional starting learning neural networks are local to able with hierarchical process perform a | Convolutional neural networks are able to perform a hierarchical learning process starting with local features. | 39,012 |
features However, attention paid a to is like limited level elementary enhancing edges. such | However, a limited attention is paid to enhancing such elementary level features like edges. | 39,013 |
transmission. of misclassification community of community-onset role underplays the and cases Underreporting systematic | Underreporting of community-onset cases and systematic misclassification underplays the role of community transmission. | 39,014 |
Harmonic, by Heronian Geometric, means have been Arithmetic, and Contraharmonic mathematicians. many studied | Harmonic, Geometric, Arithmetic, Heronian and Contraharmonic means have been studied by many mathematicians. | 39,015 |
on image superior Convolutional performance recent Neural depth single have in Networks years. estimation demonstrated | Convolutional Neural Networks have demonstrated superior performance on single image depth estimation in recent years. | 39,016 |
The combines dilated ResNet and DFE convolutions. | The DFE combines ResNet and dilated convolutions. | 39,017 |
input from multi-scale extracts keeping while information maps feature image It dense. the | It extracts multi-scale information from input image while keeping the feature maps dense. | 39,018 |
attention DMG, we features multi-scale DFE. As to for in mechanism fuse use produced | As for DMG, we use attention mechanism to fuse multi-scale features produced in DFE. | 39,019 |
is any does Network need Our and trained post-processing. not end-to-end | Our Network is trained end-to-end and does not need any post-processing. | 39,020 |
this an domain brings option. appealing adaptation setting, In | In this setting, domain adaptation brings an appealing option. | 39,021 |
give Conservative studies Ablation the insights more properties into Loss. of | Ablation studies give more insights into properties of the Conservative Loss. | 39,022 |
method a images introduce learning perturbations for adversarial to or individual targeted We videos. | We introduce a method for learning adversarial perturbations targeted to individual images or videos. | 39,023 |
data This discussed in prospective of augmentation terms a is scheme. | This is discussed in terms of a prospective data augmentation scheme. | 39,024 |
for yet high-quality perturbations also sparse The or be video leveraged compression. image may | The sparse yet high-quality perturbations may also be leveraged for image or video compression. | 39,025 |
this generalizing learn discriminant The to views. representations across is view-invariant to well key problem | The key to this problem is to learn discriminant view-invariant representations generalizing well across views. | 39,026 |
on results that datasets the show outperforms four Experimental our approach state-ofthe-art multiview approaches. | Experimental results on four multiview datasets show that our approach outperforms the state-ofthe-art approaches. | 39,027 |
and detail procedure. in paper evaluation the This presents dataset | This paper presents in detail the dataset and evaluation procedure. | 39,028 |
The with for directions paper concludes improvements. future | The paper concludes with directions for future improvements. | 39,029 |
can Sensing scenario during medical the the safety operations. ensure the surgical | Sensing the medical scenario can ensure the safety during the surgical operations. | 39,030 |
follows. work contributions as our of are The key | The key contributions of our work are as follows. | 39,031 |
Systems have convolutional perform remarkable manipulation achieved realism. networks deep image that using | Systems that perform image manipulation using deep convolutional networks have achieved remarkable realism. | 39,032 |
despite applications pose large require changing precise Many environments. and estimates operating in robotics | Many robotics applications require precise pose estimates despite operating in large and changing environments. | 39,033 |
biology Diffusion important is cell and in complicated. | Diffusion in cell biology is important and complicated. | 39,034 |
to additional as leverage signals. consistency geometric supervisory In propose we this paper, | In this paper, we propose to leverage geometric consistency as additional supervisory signals. | 39,035 |
favorably methods. that our compare unsupervised and depth state-of-the-art Extensive demonstrate flow experiments with models | Extensive experiments demonstrate that our depth and flow models compare favorably with state-of-the-art unsupervised methods. | 39,036 |
It this roadmap issue. tackle general presented a to | It presented a general roadmap to tackle this issue. | 39,037 |
well The samples the of when cGAN even works training are limited. number | The cGAN works well even when the number of training samples are limited. | 39,038 |
Therefore, the approaches. several outperforms proposed method state-of-the-art | Therefore, the proposed method outperforms several state-of-the-art approaches. | 39,039 |
shown capability intelligence artificial tasks. various of Convolutional networks (CNNs) have solving great neural | Convolutional neural networks (CNNs) have shown great capability of solving various artificial intelligence tasks. | 39,040 |
in the However, applications. raised in resource-limited has model challenges employing them increasing size | However, the increasing model size has raised challenges in employing them in resource-limited applications. | 39,041 |
this Based light-weight operation, we ChannelNets. CNNs build known as novel on | Based on this novel operation, we build light-weight CNNs known as ChannelNets. | 39,042 |
fibrillation. and arrhythmias dangerous synchronisation underlie fatal regime of abnormal self-organised Cardiac re-entry | Cardiac re-entry regime of self-organised abnormal synchronisation underlie dangerous arrhythmias and fatal fibrillation. | 39,043 |
models Re-entry cardiac prescribed of the is locations mono-domain spatially tissue. initiated homogeneous at in | Re-entry is initiated at prescribed locations in the spatially homogeneous mono-domain models of cardiac tissue. | 39,044 |
and consequently, they some to However, occur are automatically. traffic rarely recognize difficult signs | However, some traffic signs occur rarely and consequently, they are difficult to recognize automatically. | 39,045 |
keypoints has in presence the an detecting be of unresolved to blur remained issue. However, | However, detecting keypoints in the presence of blur has remained to be an unresolved issue. | 39,046 |
limited performance. a result, have those methods As | As a result, those methods have limited performance. | 39,047 |
make scale-robust, it also to scale it To space. extend we | To make it scale-robust, we also extend it to scale space. | 39,048 |
acceptance.} the will any our publicly our Without parallelization, upon available make code implementation\footnote{We | Without any parallelization, our implementation\footnote{We will make our code publicly available upon the acceptance.} | 39,049 |
of results process, co-decision by acquired the classification learners. testing are During two | During testing process, classification results are acquired by co-decision of the two learners. | 39,050 |
However, is label an process. expensive and time-consuming collection | However, label collection is an expensive and time-consuming process. | 39,051 |
addition, view-adversarial propose In to training method view-invariant a we of learning features. enhance | In addition, we propose a view-adversarial training method to enhance learning of view-invariant features. | 39,052 |
of recognition the We representations datasets. on demonstrate the action learned effectiveness for multiple | We demonstrate the effectiveness of the learned representations for action recognition on multiple datasets. | 39,053 |
method we generic, images. segmentation blood vessels our for Though apply of in retinal fundus | Though generic, we apply our method for segmentation of blood vessels in retinal fundus images. | 39,054 |
extraction. framework, for architecture CNN the spectrograms single In is a onto applied feature multiple | In the framework, a single CNN architecture is applied onto multiple spectrograms for feature extraction. | 39,055 |
then fused spectrograms The acoustic extracted from features the to scenes. multiple discriminate are deep | The deep features extracted from multiple spectrograms are then fused to discriminate the acoustic scenes. | 39,056 |
Experimental accuracies proposed that achieve show the on can results method both promising datasets. | Experimental results show that the proposed method can achieve promising accuracies on both datasets. | 39,057 |
structures enhanced can introduce into acid functionalities and base Incorporating metal-mediated stabilities. pairs nucleic new | Incorporating metal-mediated base pairs into nucleic acid structures can introduce new functionalities and enhanced stabilities. | 39,058 |
G-duplexes are linear rigid B-DNA. more IMS than indicates that and | IMS indicates that G-duplexes are linear and more rigid than B-DNA. | 39,059 |
used to with propose the experiments. were IMS compatible structures calculations DFT | DFT calculations were used to propose structures compatible with the IMS experiments. | 39,060 |
and Extensive performance experiments of demonstrate MDCN models. the the over effectiveness state-of-the-art superior | Extensive experiments demonstrate the effectiveness and superior performance of MDCN over the state-of-the-art models. | 39,061 |
the solved CCMDP, The in problems be so approach states efficiently. decouples can large that | The approach decouples states in the CCMDP, so that large problems can be solved efficiently. | 39,062 |
estimators empirical assessed of proposed The an usefulness the in example. is | The usefulness of the proposed estimators is assessed in an empirical example. | 39,063 |
of is important and images most one operations editing videos. Compositing for the | Compositing is one of the most important editing operations for images and videos. | 39,064 |
The called of realism is composite of harmonization. process the improving often results | The process of improving the realism of composite results is often called harmonization. | 39,065 |
mainly Previous images. on focus harmonization for approaches | Previous approaches for harmonization mainly focus on images. | 39,066 |
this attack In work, step to the of harmonization. further we video one take problem | In this work, we take one step further to attack the problem of video harmonization. | 39,067 |
well show on that composite dataset. synthetic the training our to dataset Experiments real-world generalizes | Experiments show that training on our synthetic dataset generalizes well to the real-world composite dataset. | 39,068 |
and significant pose motion, challenges. However, date, occlusions motion fast to blur | However, to date, fast motion, motion blur and occlusions pose significant challenges. | 39,069 |
to for features depth. represent hint these may predict important Hence, learning an | Hence, these features may represent an important hint for learning to predict depth. | 39,070 |
these blur we depth-prediction studies, out-of-focus that improves From performances. greatly the show network | From these studies, we show that out-of-focus blur greatly improves the depth-prediction network performances. | 39,071 |
visual Contrast information is in processing. crucial a factor | Contrast is a crucial factor in visual information processing. | 39,072 |
directions of provide topic. in this emerging future research further possible We | We further provide possible directions of future research in this emerging topic. | 39,073 |
intrinsic with we information an model within-person its identity a variations. face First, and representation | First, we model a face representation with an intrinsic identity information and its within-person variations. | 39,074 |
paper access This (MEC) non-orthogonal investigates uplink multiple mobile-edge an network. (NOMA)-based computing | This paper investigates an uplink non-orthogonal multiple access (NOMA)-based mobile-edge computing (MEC) network. | 39,075 |
shown be optimal. algorithm The is proposed successfully globally to | The proposed algorithm is successfully shown to be globally optimal. | 39,076 |
the results better than show performance methods. algorithm proposed achieves Numerical that the conventional | Numerical results show that the proposed algorithm achieves better performance than the conventional methods. | 39,077 |
communication communication the integrated The wireless is in generation networks. promising next radar and system | The integrated radar and communication system is promising in the next generation wireless communication networks. | 39,078 |
energy. However, by confined its performance is limited the | However, its performance is confined by the limited energy. | 39,079 |
proposed. wireless it, and to radar overcome communication system powered order In integrated a is | In order to overcome it, a wireless powered integrated radar and communication system is proposed. | 39,080 |
problem subject minimization performances. constraints formulated radar to the and on is communication An energy | An energy minimization problem is formulated subject to constraints on the radar and communication performances. | 39,081 |
optimized energy energy. jointly beamforming to The waveform are radar-communication the minimize consumption and | The energy beamforming and radar-communication waveform are jointly optimized to minimize the consumption energy. | 39,082 |
solved challenging variable relaxation by is using non-convex The and problem auxiliary methods. semidefinite | The challenging non-convex problem is solved by using semidefinite relaxation and auxiliary variable methods. | 39,083 |
It is obtained. proved solution optimal that be can the | It is proved that the optimal solution can be obtained. | 39,084 |
proposed results Simulation our benchmark scheme. outperforms optimal the design demonstrate that | Simulation results demonstrate that our proposed optimal design outperforms the benchmark scheme. | 39,085 |
lesion results in skin models automated show remarkable analysis. learning Deep | Deep learning models show remarkable results in automated skin lesion analysis. | 39,086 |
input expand transforming by dataset training Data images. can the augmentation | Data augmentation can expand the training dataset by transforming input images. | 39,087 |
GO-CNN on stability. amount reduces and examples enhances the Furthermore, adversarial dependence of training | Furthermore, GO-CNN reduces dependence on the amount of training examples and enhances adversarial stability. | 39,088 |
addresses paper optimal sampling the set selecting for problem on graphs. This an of signals | This paper addresses the problem of selecting an optimal sampling set for signals on graphs. | 39,089 |
through execution our the We performance errors approach evaluate time. of and prediction comparisons of | We evaluate the performance of our approach through comparisons of prediction errors and execution time. | 39,090 |
this from suffers still great limitations. framework success, several Despite the tracking | Despite the great success, this tracking framework still suffers from several limitations. | 39,091 |
it object large cannot First, properly handle rotation. | First, it cannot properly handle large object rotation. | 39,092 |
distracted Second, gets salient the background objects. contains tracking when easily | Second, tracking gets easily distracted when the background contains salient objects. | 39,093 |
Increasing existing thumbnail capabilities direction. compression research codecs of an beyond is therefore the active | Increasing thumbnail compression beyond the capabilities of existing codecs is therefore an active research direction. | 39,094 |
triangles. present we the algorithm for Second, novel encoding a | Second, we present a novel algorithm for encoding the triangles. | 39,095 |
identifying by for promising research. future survey We finish the directions | We finish the survey by identifying promising directions for future research. | 39,096 |
has transfer learning acquired interest. recently Deep research significant | Deep transfer learning recently has acquired significant research interest. | 39,097 |
deep Model-based probably used most transfer the is method. frequently learning | Model-based deep transfer learning is probably the most frequently used method. | 39,098 |
approach, learning features. useful help learning more Using can transfer models to deep capture this | Using this approach, transfer learning can help deep learning models to capture more useful features. | 39,099 |
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