text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
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we problem properties generator. rethink make this paper, of In the a proposal good what | In this paper, we rethink the problem of what properties make a good proposal generator. | 35,100 |
an social human-computer interaction. non-verbal processing and behavior Gaze in important is cue signal | Gaze behavior is an important non-verbal cue in social signal processing and human-computer interaction. | 35,101 |
in computations. The is executing extremely data-extensive challenge their biggest DNNs | The biggest challenge in executing DNNs is their extremely data-extensive computations. | 35,102 |
data the deployment. directly networks quantizing %However, accuracy deep is in by limited system | %However, the system accuracy is limited by quantizing data directly in deep networks deployment. | 35,103 |
Previous inter-layer mainly works signals neglected. discretize on mainly weights while are focus | Previous works mainly focus on weights discretize while inter-layer signals are mainly neglected. | 35,104 |
example. the DNNs system implement memristor-based a proposed on the SNC We deployment as | We implement the proposed DNNs on the memristor-based SNC system as a deployment example. | 35,105 |
of finite previously a neurons. for uniform We size effects globally developed theory coupled generalize | We generalize a previously developed theory of finite size effects for uniform globally coupled neurons. | 35,106 |
discriminative an are and around object? views where But informative such | But where are such informative and discriminative views around an object? | 35,107 |
and venues. this work, travel are as destination location In taken business | In this work, travel destination and business location are taken as venues. | 35,108 |
by is applications. very a Discovering important for a photo venue context-aware | Discovering a venue by a photo is very important for context-aware applications. | 35,109 |
data. heterogeneous discovery goal venue multimodal is Our fine-grained from social | Our goal is fine-grained venue discovery from heterogeneous social multimodal data. | 35,110 |
on proposed the of confirm method. results feasibility the this Experimental dataset | Experimental results on this dataset confirm the feasibility of the proposed method. | 35,111 |
estimates likelihood marginal unbiased. is An additional benefit are that | An additional benefit is that marginal likelihood estimates are unbiased. | 35,112 |
AU. The of determined the Gaussian is size the of the and by amplitude intensity | The amplitude and size of the Gaussian is determined by the intensity of the AU. | 35,113 |
has bandstop A in proposed varactor-based been article. tunable filter this | A varactor-based tunable bandstop filter has been proposed in this article. | 35,114 |
have networks classification. neural used Convolutional for widely image (CNNs) been | Convolutional neural networks (CNNs) have been widely used for image classification. | 35,115 |
propose novel we a improve convolutional the To learning prototype (CPL). learning robustness, framework called | To improve the robustness, we propose a novel learning framework called convolutional prototype learning (CPL). | 35,116 |
train classification we to criteria of CPL, framework the design the Under multiple network. | Under the framework of CPL, we design multiple classification criteria to train the network. | 35,117 |
Positive geometry matrices covariance The of of (SPD) that space Definite matrices. the Symmetric is | The space geometry of the covariance matrices is that of Symmetric Positive Definite (SPD) matrices. | 35,118 |
systems Automated rely vehicles. proper passing on classification toll the of | Automated toll systems rely on proper classification of the passing vehicles. | 35,119 |
vehicle. whole obtain about To the information | To obtain information about the whole vehicle. | 35,120 |
Existing interactive as promising approaches venue. a propose search image | Existing approaches propose interactive image search as a promising venue. | 35,121 |
three and datasets baselines three experimental We extensive on outperform settings. | We outperform three baselines on three datasets and extensive experimental settings. | 35,122 |
this interpretation. with comes of approach complications However, | However, this approach comes with complications of interpretation. | 35,123 |
Optimal parameter Instrumental Linear The approximation the (OLIVA). in called Variables the Approximation is linear | The parameter in the linear approximation is called the Optimal Linear Instrumental Variables Approximation (OLIVA). | 35,124 |
instrument is in unknown the be identified. The estimand not may IV and | The instrument in the IV estimand is unknown and may not be identified. | 35,125 |
discuss least We also to weighted criteria. extensions squares | We also discuss extensions to weighted least squares criteria. | 35,126 |
excellent suggest performance an simulations finite sample the Carlo for proposed inferences. Monte | Monte Carlo simulations suggest an excellent finite sample performance for the proposed inferences. | 35,127 |
set a is At training-time, filters. explicit the boundary with provided of network separate | At training-time, the network is provided with a separate set of explicit boundary filters. | 35,128 |
tracking in a compared plays role performance trackers. Correlation major filter existing improved to | Correlation filter plays a major role in improved tracking performance compared to existing trackers. | 35,129 |
The the tracker of the to location predict correlation the response target. uses adaptive | The tracker uses the adaptive correlation response to predict the location of the target. | 35,130 |
frame were proposed accuracy high correlation recently varieties of and trackers with rates. Many | Many varieties of correlation trackers were proposed recently with high accuracy and frame rates. | 35,131 |
approach validated sequences. Benchmark Tracking Object is The using | The approach is validated using Object Tracking Benchmark sequences. | 35,132 |
The optimize frame-wise usually likelihood the employ maximal existing a models. to loss methods | The existing methods usually employ a frame-wise maximal likelihood loss to optimize the models. | 35,133 |
can that performance. recognition text substantially boost show scene Experimental EP results the | Experimental results show that the EP can substantially boost scene text recognition performance. | 35,134 |
constraint specific search requires good problems of often heuristics. or Effective choosing solving | Effective solving of constraint problems often requires choosing good or specific search heuristics. | 35,135 |
is to heuristics give search robust which automatic The goal performance. obtain | The goal is to obtain automatic search heuristics which give robust performance. | 35,136 |
our adaptive than technique experiments is original heuristics. more show that the robust Preliminary search | Preliminary experiments show that our adaptive technique is more robust than the original search heuristics. | 35,137 |
outperform the also heuristics. can original It | It can also outperform the original heuristics. | 35,138 |
Using reduction, analysis. significant we PWM-based dimension identify subspaces for | Using dimension reduction, we identify significant PWM-based subspaces for analysis. | 35,139 |
ML-based sequence PWM-based These subspaces tool. an form analysis | These PWM-based subspaces form an ML-based sequence analysis tool. | 35,140 |
improved the TFs. on performance mammalian It also | It also improved the performance on mammalian TFs. | 35,141 |
easily to tools PWM-based future well information. as is more as The include extendable ensemble | The ensemble is easily extendable to include more tools as well as future PWM-based information. | 35,142 |
personalized full Reaching the on precision of genome of interpretation. the medicine potential depends quality | Reaching the full potential of precision medicine depends on the quality of personalized genome interpretation. | 35,143 |
the compared better the original that achieve results results show proposed with Evaluation FlowNet. network | Evaluation results show that the proposed network achieve better results compared with the original FlowNet. | 35,144 |
This block-matching optical flow called proposes (ABMOF). algorithm event-driven adaptive OF an paper | This paper proposes an event-driven OF algorithm called adaptive block-matching optical flow (ABMOF). | 35,145 |
ABMOF accumulated events. time of uses slices DVS | ABMOF uses time slices of accumulated DVS events. | 35,146 |
results. The OF based time slices adaptively input events are on rotated the and | The time slices are adaptively rotated based on the input events and OF results. | 35,147 |
conventional standards as Lucas-Kanade Results such achieves accuracy (LK). comparable show that to ABMOF | Results show that ABMOF achieves comparable accuracy to conventional standards such as Lucas-Kanade (LK). | 35,148 |
implemented. our adapted using also is An slices LK method | An LK method using our adapted slices is also implemented. | 35,149 |
strategies influence and this sampling conformational how explore space how might predictions? do Namely, | Namely, how do sampling strategies explore conformational space and how might this influence predictions? | 35,150 |
we kinetics. compare in describing thermodynamics MSM Additionally, and estimators | Additionally, we compare MSM estimators in describing thermodynamics and kinetics. | 35,151 |
dilated equipped we convolutional blocks a different generic classification of Then, with rates. network design | Then, we design a generic classification network equipped with convolutional blocks of different dilated rates. | 35,152 |
obtains apparent performance approach Despite state-of-the-arts. over proposed the our superior simplicity, | Despite the apparent simplicity, our proposed approach obtains superior performance over state-of-the-arts. | 35,153 |
of different facial landmarks. distortions into expressions categories facial requires capturing regional Classifying | Classifying facial expressions into different categories requires capturing regional distortions of facial landmarks. | 35,154 |
best are of results results aware these are Both we the of. | Both of these results are the best results we are aware of. | 35,155 |
considered. for adaptive is worst-case problem robust The beamforming signal general-rank model | The worst-case robust adaptive beamforming problem for general-rank signal model is considered. | 35,156 |
algorithm to Herein inner second-order it. solve an is (SOCP) proposed cone approximate program | Herein an inner second-order cone program (SOCP) approximate algorithm is proposed to solve it. | 35,157 |
relaxation does result, computationally As a technique. algorithm heavy SDP use not our | As a result, our algorithm does not use computationally heavy SDP relaxation technique. | 35,158 |
significance fundus doctors The retinal vessels of segmentation to diseases. for diagnose of the is | The segmentation of retinal vessels is of significance for doctors to diagnose the fundus diseases. | 35,159 |
the mainly generator. We structure the network improve of | We mainly improve the network structure of the generator. | 35,160 |
multiple in has enjoyed years. Reinforcement learning recent successes | Reinforcement learning has enjoyed multiple successes in recent years. | 35,161 |
in is topic Parsimony signal active representation a research. of | Parsimony in signal representation is a topic of active research. | 35,162 |
a conditional GAN model HiGAN \emph{high-level} of \emph{low-level} consists conditional The a GAN. and | The HiGAN model consists of a \emph{low-level} conditional GAN and a \emph{high-level} conditional GAN. | 35,163 |
(i.e. datasets experiments on recognition Comprehensive video two challenging | Comprehensive experiments on two challenging video recognition datasets (i.e. | 35,164 |
better? by Inspired we advancement, asked do ourselves, such can we | Inspired by such advancement, we asked ourselves, can we do better? | 35,165 |
Networks (DCNet) propose We (DCNet++). and Networks Diverse Capsule Capsule Dense | We propose Dense Capsule Networks (DCNet) and Diverse Capsule Networks (DCNet++). | 35,166 |
in different maps This primary forming in the incorporating layers helps capsules. learned by feature | This helps in incorporating feature maps learned by different layers in forming the primary capsules. | 35,167 |
network, which deeper adds essentially leads to of feature discriminative DCNet, maps. convolution a learning | DCNet, essentially adds a deeper convolution network, which leads to learning of discriminative feature maps. | 35,168 |
classification on the architectures. of efficacy using proposed Experiments image task datasets demonstrate the benchmark | Experiments on image classification task using benchmark datasets demonstrate the efficacy of the proposed architectures. | 35,169 |
wind the forecasts. of This around on energy confidence construction aims bands work | This work aims on the construction of confidence bands around wind energy forecasts. | 35,170 |
'open (e.g. and differing distinguish ones door', 'open cupboard'), | 'open door', 'open cupboard'), and distinguish differing ones (e.g. | 35,171 |
vs verb-only 'open labels. 'open door' using bottle') | 'open door' vs 'open bottle') using verb-only labels. | 35,172 |
legitimate ambiguities class (Fig. Current between approaches recognition and for verbs neglect action semantic overlaps | Current approaches for action recognition neglect legitimate semantic ambiguities and class overlaps between verbs (Fig. | 35,173 |
two-stream learn multi-output fusion using regression, CNN. these as We a representations | We learn these representations as multi-output regression, using a two-stream fusion CNN. | 35,174 |
Finally, real evaluate collected framework using data. we developed effectiveness our the of vehicle the | Finally, we evaluate the effectiveness of our developed framework using the collected real vehicle data. | 35,175 |
wavelet identification neural nonlinear system. network online of performs the (WNN) The the | The wavelet neural network (WNN) performs the online identification of the nonlinear system. | 35,176 |
is prove to used the theory the of The MPC. stability Lyapunov | The Lyapunov theory is used to prove the stability of the MPC. | 35,177 |
vehicle. unmanned We control methodology identification online of an the apply the and to autonomous | We apply the methodology to the online identification and control of an unmanned autonomous vehicle. | 35,178 |
time videos is for this longer However, consuming. very | However, for longer videos this is very time consuming. | 35,179 |
produce accurate architectures deep datasets. Modern on highly learning segmentation challenging many semantic results | Modern deep learning architectures produce highly accurate results on many challenging semantic segmentation datasets. | 35,180 |
neonates Limited-channel of analytic by lack research in is open, tools. Goal: accessible hindered EEG | Goal: Limited-channel EEG research in neonates is hindered by lack of open, accessible analytic tools. | 35,181 |
three experienced by validated was The reviewers. aEEG algorithm | The aEEG algorithm was validated by three experienced reviewers. | 35,182 |
reviewers background classification. Using methodology, a pattern assigned standard | Using standard methodology, reviewers assigned a background pattern classification. | 35,183 |
using Pearson's coefficient. Results compared were correlation | Results were compared using Pearson's correlation coefficient. | 35,184 |
the work the reduces manual facilitates and identity processing. of It recognition automatic | It reduces the manual work of identity recognition and facilitates the automatic processing. | 35,185 |
the from the data. layers features learns intermediate CNN The automatically hierarchical at | The CNN learns the hierarchical features at intermediate layers automatically from the data. | 35,186 |
does paper for performance anti-spoofing. This CNNs face of evaluation a | This paper does a performance evaluation of CNNs for face anti-spoofing. | 35,187 |
and The CNN are used this ResNet Inception study. architectures in | The Inception and ResNet CNN architectures are used in this study. | 35,188 |
Spoofing results are Database. Face MSU Mobile computed over The benchmark | The results are computed over benchmark MSU Mobile Face Spoofing Database. | 35,189 |
The in for face results using these settings. different obtained favorable anti-spoofing CNN architectures are | The favorable results are obtained using these CNN architectures for face anti-spoofing in different settings. | 35,190 |
a machine model. replacement to We this apply estimator | We apply this estimator to a machine replacement model. | 35,191 |
to challenging Hierarchical is approach these learning a able that is principled reinforcement tackle tasks. | Hierarchical reinforcement learning is a principled approach that is able to tackle these challenging tasks. | 35,192 |
hierarchical learning POMDP. We propose reinforcement approach a in hierarchical for learning deep | We propose a hierarchical deep reinforcement learning approach for learning in hierarchical POMDP. | 35,193 |
The RL is hierarchical to apply MDP learning. proposed to algorithm deep POMDP and both | The deep hierarchical RL algorithm is proposed to apply to both MDP and POMDP learning. | 35,194 |
evaluate We hierarchical challenging the algorithm proposed various POMDP. on | We evaluate the proposed algorithm on various challenging hierarchical POMDP. | 35,195 |
tasks scene visual are parsing understanding. estimation two Depth in particularly and scene important | Depth estimation and scene parsing are two particularly important tasks in visual scene understanding. | 35,196 |
challenging are datasets conducted two (i.e. on experiments Extensive | Extensive experiments are conducted on two challenging datasets (i.e. | 35,197 |
novel paper method presents for correspondence. cross-domain sparse a This | This paper presents a novel method for sparse cross-domain correspondence. | 35,198 |
input unorganized data. perspective five network of point representations the of cloud The consists | The network input consists of five perspective representations of the unorganized point cloud data. | 35,199 |
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