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efficacy in in The attributes view acquisition. synaptic memory to changes neuroscience prevailing
The prevailing view in neuroscience attributes changes in synaptic efficacy to memory acquisition.
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view to stable This memories correspond implies connectivity stable that patterns.
This view implies that stable memories correspond to stable connectivity patterns.
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significant, activity-independent However, of to body an evidence increasing synaptic in dynamics strengths. experimental points
However, an increasing body of experimental evidence points to significant, activity-independent dynamics in synaptic strengths.
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memories more plasticity are imaginary-coded to noise Specifically, resilient and real-coded than their counterparts. homeostatic
Specifically, imaginary-coded memories are more resilient to noise and homeostatic plasticity than their real-coded counterparts.
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on complex In using networks. hierarchical work, neural natural more images focus this unsupervised we
In this work, we focus on more complex natural images using unsupervised hierarchical neural networks.
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problematic when in conditions. segmentation imaging outdoor is there of Semantic are variations scenes
Semantic segmentation of outdoor scenes is problematic when there are variations in imaging conditions.
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known is (reflectance) of that effects. albedo illumination to is invariant It all kinds
It is known that albedo (reflectance) is invariant to all kinds of illumination effects.
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images task be can Thus, segmentation reflectance using favorable. semantic for
Thus, using reflectance images for semantic segmentation task can be favorable.
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We of two those analyze the addressing gains jointly. problems
We analyze the gains of addressing those two problems jointly.
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single tasks. architectures cascade and new for segmentation-for-intrinsic as CNN proposed are intrinsic-for-segmentation Moreover,
Moreover, new cascade CNN architectures for intrinsic-for-segmentation and segmentation-for-intrinsic are proposed as single tasks.
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detail and these going statistical mathematical Here, the by through framework. we steps
Here, we detail these steps by going through the mathematical and statistical framework.
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understanding be We the can of explain it applied \beta-arrestin-dependent networks. to signaling how
We explain how it can be applied to the understanding of \beta-arrestin-dependent signaling networks.
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graph matches. cost Edges the of these the of represent
Edges of the graph represent the cost of these matches.
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is essential protocols for networks. and evaluation Channel in design modeling numerous performance of vehicular
Channel modeling is essential for design and performance evaluation of numerous protocols in vehicular networks.
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An performance ultra-wideband to optical in model estimate presented. analytical transmission networks nonlinear is
An analytical model to estimate nonlinear performance in ultra-wideband optical transmission networks is presented.
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to Sequential previously search neural for its architectures classification. capabilities demonstrated has find image state-of-the-art
Sequential search has previously demonstrated its capabilities to find state-of-the-art neural architectures for image classification.
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computational remains even computational under unreachable high, its modest cost settings. However,
However, its computational cost remains high, even unreachable under modest computational settings.
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weight-sharing Affording SMBO with problem. this alleviates
Affording SMBO with weight-sharing alleviates this problem.
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rank used is sampled to prediction directly the neural architectures. This
This prediction is directly used to rank the sampled neural architectures.
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is SEM problem, solve an mitigation this To described. scheme
To solve this problem, an SEM mitigation scheme is described.
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thus However, pilot accurate estimations, better can performance. more achieve the system
However, the pilot system can achieve more accurate estimations, thus better performance.
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intermediate an view, introduced large is view, gap. First, i.e., the homography to bridge
First, an intermediate view, i.e., homography view, is introduced to bridge the large gap.
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discussions its cases. studies some in robustness and reliability show challenging Ablation and
Ablation studies and discussions show its reliability and robustness in some challenging cases.
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brain lesion are for learning Deep used methods actively segmentation.
Deep learning methods are actively used for brain lesion segmentation.
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patch-sampling We new propose small increase lesions. procedure for performance a to network
We propose a new patch-sampling procedure to increase network performance for small lesions.
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show both solid cases. results The experimental in improvements
The experimental results show solid improvements in both cases.
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and feature has scalability learning engineering on issues. machine directly graphs, needs However,
However, machine learning directly on graphs, needs feature engineering and has scalability issues.
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proposes on based novel This image. paper image single method fusion a pseudo a multi-exposure
This paper proposes a novel pseudo multi-exposure image fusion method based on a single image.
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proposed enables The method pseudo from images to produce multi-exposure single us image. a
The proposed method enables us to produce pseudo multi-exposure images from a single image.
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conventional multi-exposure proposed to multi-exposure images. image Most methods applicable the are fusion also of
Most of conventional multi-exposure image fusion methods are also applicable to the proposed multi-exposure images.
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synthetic and Experiments the proposed both promising on performance the of validate architecture real datasets.
Experiments validate the promising performance of the proposed architecture on both synthetic and real datasets.
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method deconvolution we (FBD). call blind Hence the focused
Hence we call the method focused blind deconvolution (FBD).
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relaxed constraints The progress. iterations the focusing are as
The focusing constraints are relaxed as the iterations progress.
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Learning their classification more classification including power elaborate competes methods. Deep approaches Furthermore, with
Furthermore, their classification power competes with more elaborate classification approaches including Deep Learning methods.
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to methods. no evaluate However, the and endoscopy aforementioned compare objective criteria are there
However, there are no objective criteria to evaluate and compare the aforementioned endoscopy methods.
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consistent studies. is the observation clinical This with
This observation is consistent with the clinical studies.
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the effectiveness of proposed demonstrated. is the criterion Therefore,
Therefore, the effectiveness of the proposed criterion is demonstrated.
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features visual object-agnostic Therefore, models. we learning relationship generalizable more in are interested for
Therefore, we are interested in learning object-agnostic visual features for more generalizable relationship models.
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propose the novel strategy. \texttt{Shuffle-Then-Assemble} To pre-training alleviate a we bias,
To alleviate the bias, we propose a novel \texttt{Shuffle-Then-Assemble} pre-training strategy.
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will ecological to nonlinear biological parameters models an Identifiability consider. of be issue in
Identifiability of biological parameters in nonlinear ecological models will be an issue to consider.
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reconstruction a We propose (cGANs). direct conditional based on adversarial fingerprint model networks latent generative
We propose a direct latent fingerprint reconstruction model based on conditional generative adversarial networks (cGANs).
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been solver top ASP the of WASP. on has The approach implemented
The approach has been implemented on top of the ASP solver WASP.
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(TPLP). and of Under consideration Programming Logic Practice in Theory
Under consideration in Theory and Practice of Logic Programming (TPLP).
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Here discuss nature the of models network neuroscience. in we
Here we discuss the nature of network models in neuroscience.
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base artificial an Knowledge important (KB) intelligence. is aspect in
Knowledge base (KB) is an important aspect in artificial intelligence.
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bases and proposed approaches that efficiently results cleanse the Experimental effectively. knowledge the demonstrate could
Experimental results demonstrate that the proposed approaches could cleanse the knowledge bases efficiently and effectively.
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network architectures, attacks these weak transferability neural Additionally, e.g. across demonstrate cross-network
Additionally, these attacks demonstrate weak cross-network transferability across neural network architectures, e.g.
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the semantic of addresses dense problem work This scene under understanding fog.
This work addresses the problem of semantic scene understanding under dense fog.
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methods outdoor recognition weather conditions to Extending crucial such fog as for applications. is adverse
Extending recognition methods to adverse weather conditions such as fog is crucial for outdoor applications.
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The code and publicly are datasets available.
The datasets and code are publicly available.
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for to correct it difficult These radiologists render diagnostic artifacts make decisions.
These artifacts make it difficult for radiologists to render correct diagnostic decisions.
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videos This visual an in from learning unsupervised necessitates features setting. of
This necessitates learning of visual features from videos in an unsupervised setting.
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The following framework. also step in charts is unnecessary our packing
The following charts packing step is also unnecessary in our framework.
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more map efficient. technique the and practical normal makes is and robust Our method
Our method is practical and makes the normal map technique more robust and efficient.
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individual arrangement. their appears parts Structure typically of the and form in
Structure typically appears in the form of individual parts and their arrangement.
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incomplete information scans. structural templates and onto transfer objects new us the allow to The
The templates allow us to transfer the structural information onto new objects and incomplete scans.
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of other method state-of-the-art our showcase the We by comparing approaches. effectiveness it to
We showcase the effectiveness of our method by comparing it to other state-of-the-art approaches.
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Diverse utilized improve been information the auxiliary feature has visual learning. to
Diverse auxiliary information has been utilized to improve the visual feature learning.
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birth. induced within the When crest pups at die neural lineage,
When induced within the neural crest lineage, pups die at birth.
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derivatives crest appear the unaffected. Neural body in
Neural crest derivatives in the body appear unaffected.
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propagation may Its unmixing of in significant occurrence the the process. estimation to errors lead
Its occurrence may lead to the propagation of significant estimation errors in the unmixing process.
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a from present human avatar method novel for monocular We creation detail-preserving video. high
We present a novel method for high detail-preserving human avatar creation from monocular video.
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garment wrinkles, Our avatars clothes a high-resolution and texture. with face, hairstyle, feature natural
Our avatars feature a natural face, hairstyle, clothes with garment wrinkles, and high-resolution texture.
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the Numerous of results versatility robustness show method. our and
Numerous results show the robustness and versatility of our method.
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electroencephalography of important systems. the The is brain-computer component classifier based most interface
The electroencephalography classifier is the most important component of brain-computer interface based systems.
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it. of hindering are improvement problems the two There major
There are two major problems hindering the improvement of it.
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multimodal fully do methods not traditional First, exploit information.
First, traditional methods do not fully exploit multimodal information.
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learning two these we a transfer problems. propose novel solve deep to Herein, approach
Herein, we propose a novel deep transfer learning approach to solve these two problems.
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paper problem This of environments. addresses the head in crowded detection
This paper addresses the problem of head detection in crowded environments.
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pedestrian levels. the an method setting density with We in outdoor validate varying
We validate the method in an outdoor setting with varying pedestrian density levels.
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field. requires Semantic sizeable information receptive and segmentation both rich spatial
Semantic segmentation requires both rich spatial information and sizeable receptive field.
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address this (BiSeNet). In paper, novel Bilateral we Network this with a dilemma Segmentation
In this paper, we address this dilemma with a novel Bilateral Segmentation Network (BiSeNet).
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to others' shape affective Social may and empathy relations affective states.
Social and affective relations may shape empathy to others' affective states.
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stimuli could equally face identifiable. sizes that the of Results suggested two be
Results suggested that face stimuli of the two sizes could be equally identifiable.
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uncertainty quantification enable for random density. the normal Rogers-Szego inputs polynomials described by wrapped
Rogers-Szego polynomials enable uncertainty quantification for random inputs described by the wrapped normal density.
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Different been to methods MOD. have proposed of categories solve
Different categories of methods have been proposed to solve MOD.
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by is unsupervised stochastic descent end-to-end an Optimization in performed and gradient fashion.
Optimization is performed by stochastic gradient descent in an end-to-end and unsupervised fashion.
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Our modes. can work batch in online and both algorithm
Our algorithm can work in both batch and online modes.
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all uses like the other In optimizer methods, the images. batch batch mode,
In the batch mode, like other batch methods, optimizer uses all the images.
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into can In online fed be optimizer. mode, the images incrementally
In online mode, images can be incrementally fed into the optimizer.
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for relevant estimation. motion segmentation Moreover, and scene flow are occlusions
Moreover, occlusions are relevant for motion segmentation and scene flow estimation.
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estimated The state-of-the-art. the boundaries motion improve over and occlusions clearly
The estimated occlusions and motion boundaries clearly improve over the state-of-the-art.
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Merr.] [Glycine step max pod is Loss (L.) soybean a key of during dehiscence
Loss of pod dehiscence is a key step during soybean [Glycine max (L.) Merr.]
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Humidity the distribution shapes alleles. of indehiscent
Humidity shapes the distribution of indehiscent alleles.
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model the is for benchmark SALSA method. state-of-the-art the The applied dataset against challenging to
The model is applied to the challenging SALSA dataset for benchmark against the state-of-the-art method.
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particular this setting, outperforms presented the e.g. formulation in Our state-of-the-art significantly
Our presented formulation outperforms the state-of-the-art significantly in this particular setting, e.g.
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Such existing using correspondences. supervised datasets are truth with often derived ground on learning descriptors
Such descriptors are often derived using supervised learning on existing datasets with ground truth correspondences.
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prohibitive. usually datasets the is cost creating such However, of
However, the cost of creating such datasets is usually prohibitive.
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weakly Our is supervised aligned. because be need images method to roughly input currently the
Our method is currently weakly supervised because the input images need to be roughly aligned.
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also images. method We on our RGB evaluated
We also evaluated our method on RGB images.
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is cluster and each Challenging respectively. firstly, of landmarks optimized are focused further landmarks
Challenging landmarks are focused firstly, and each cluster of landmarks is further optimized respectively.
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main compare the biological of to algorithmic paper search techniques sequences. The and surveys evolution
The paper surveys the evolution of main algorithmic techniques to compare and search biological sequences.
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replace discuss alignment-based expansion coming in to algorithms alignment-free We of analyses. techniques large-scale the
We discuss the expansion of alignment-free techniques coming to replace alignment-based algorithms in large-scale analyses.
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challenges. on genomics Finally, algorithmic focus associated the outline and to transition population we
Finally, we focus on the transition to population genomics and outline associated algorithmic challenges.
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datasets. viewpoint estimation enables iSPA-Net This on state-of-the-art real image to achieve performance various
This enables iSPA-Net to achieve state-of-the-art performance on various real image viewpoint estimation datasets.
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multiple of effectiveness the applications. demonstrate we for Further, approach
Further, we demonstrate effectiveness of the approach for multiple applications.
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codes proposed algorithm. To the encourage reproducible research, for our released we have
To encourage reproducible research, we have released the codes for our proposed algorithm.
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limits or using performance reconstruction usually approach alone applications. However, recovery image either in
However, using either approach alone usually limits performance in image reconstruction or recovery applications.
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promising competing state-of-the-art to performance methods. Results compared show
Results show promising performance compared to state-of-the-art competing methods.
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effective phase information to and % retrieval. phase the missing compensate achieve for
% to compensate for the missing phase information and achieve effective phase retrieval.
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