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multispectral and based This hyperspectral paper variational approach images. fusing presents a to
This paper presents a variational based approach to fusing hyperspectral and multispectral images.
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Corrections expectation about the propagation are explained. expansion by then
Corrections by expansion about the expectation propagation are then explained.
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advanced sections. explored in are some and final topics applications the Finally inference
Finally some advanced inference topics and applications are explored in the final sections.
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are This between capturing mind-wandering FC suggests fluctuations that the effects. and SC
This suggests that the fluctuations between FC and SC are capturing mind-wandering effects.
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memory It also certain problems of limitations. overcomes
It also overcomes certain problems of memory limitations.
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renewed approaches multiobjective optimization. Recently, has decomposition-based in there a evolutionary been interest for
Recently, there has been a renewed interest in decomposition-based approaches for evolutionary multiobjective optimization.
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we this the In parameters. functions investigate and behavior different scalarizing of their paper,
In this paper, we investigate the behavior of different scalarizing functions and their parameters.
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main them encoding difference schemes. among their is The
The main difference among them is their encoding schemes.
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instead considers sparsity. Different group of among points from LRR the effect SC, data
Different from SC, LRR considers the group effect among data points instead of sparsity.
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offer (i.e., Benefiting LrrSPM) property, can from the better performance. a method proposed this
Benefiting from this property, the proposed method (i.e., LrrSPM) can offer a better performance.
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\emph{Entity naturally videos Discovery} in as The tracklet posed of task be can clustering.
The task of \emph{Entity Discovery} in videos can be naturally posed as tracklet clustering.
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major TC models Bayesian for are contributions at the Our tracklet-level. first nonparametric
Our major contributions are the first Bayesian nonparametric models for TC at tracklet-level.
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functions rate. Given improve object the features, these are category-specific recognition learned combination to
Given these features, category-specific combination functions are learned to improve the object recognition rate.
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key dictionary representation. for the of a A is sparse success proper
A proper dictionary is a key for the success of sparse representation.
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sparse in dictionaries The caculated learned classification representation (SRC). are based
The learned dictionaries are caculated in sparse representation based classification (SRC).
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dictionary proposed accuracy reconstruction error the evaluate to learning and The used are classification method.
The classification accuracy and reconstruction error are used to evaluate the proposed dictionary learning method.
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q-value that outperform stratified thresholds substantially E-values. We show
We show that stratified q-value thresholds substantially outperform E-values.
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of The this is twofold. paper contribution
The contribution of this paper is twofold.
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annealing solving single-stage the method we First, and problem. effective robust simulated propose for an
First, we propose an effective and robust single-stage simulated annealing method for solving the problem.
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the and an apply design parameter we Secondly, tuning for statistically-principled methodology extensive procedure. and
Secondly, we design and apply an extensive and statistically-principled methodology for the parameter tuning procedure.
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illustrated and The trains. method proposed on experimental simulated spike is
The proposed method is illustrated on simulated and experimental spike trains.
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we described from that the Moreover, domain task benefits adaptation. show
Moreover, we show that the described task benefits from domain adaptation.
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applied Secondly, on graph layers to framework many reduction dimensionality based cascaded embedding GENet. are
Secondly, many cascaded dimensionality reduction layers based on graph embedding framework are applied to GENet.
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classify used classifier is linear Finally, dimension-reduced features. a to SVM
Finally, a linear SVM classifier is used to classify dimension-reduced features.
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for In and views. pointclouds unseen cross-view action from contrast, process recognition unknown directly we
In contrast, we directly process pointclouds for cross-view action recognition from unknown and unseen views.
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The show that Experimental methods. provide techniques over improvement significant state-of-the-art results our
The Experimental results show that our techniques provide significant improvement over state-of-the-art methods.
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novel localisation lip proposed face includes method. scheme approach The a a localisation and automatic
The proposed approach includes a novel automatic face localisation scheme and a lip localisation method.
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data large sets methods. other of proposed to on Simulations method performance the superior show
Simulations on large data sets show superior performance of the proposed method to other methods.
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state-of-the-art the by is and LSEs of laborious tuning parameter application computation. expensive compromised However,
However, the application of state-of-the-art LSEs is compromised by laborious parameter tuning and expensive computation.
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to contrast faster. LSEs are the existing In methods, proposed significantly
In contrast to existing methods, the proposed LSEs are significantly faster.
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they parameters importantly, while better Most involve performance. achieving fewer much
Most importantly, they involve much fewer parameters while achieving better performance.
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(CNNs) Networks gained Neural detection. Convolutional have and image great object success classification Deep in
Deep Convolutional Neural Networks (CNNs) have gained great success in image classification and object detection.
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studies on focus deserving issue. this However, fewer
However, fewer studies focus on this deserving issue.
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selected the to concepts in unfriendly These correspond category. image vectors each
These selected vectors correspond to the unfriendly concepts in each image category.
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compressive to cascaded sensing from feature we network use the Firstly, data. learn
Firstly, we use cascaded compressive sensing network to learn feature from the data.
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CSNet generates feature Secondly, by binary histograms. and hashing block-wise the
Secondly, CSNet generates the feature by binary hashing and block-wise histograms.
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classify features. to is used linear classifier a Finally, these SVM
Finally, a linear SVM classifier is used to classify these features.
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together the thesis. topic projects this connects This presented in
This topic connects together the projects presented in this thesis.
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transcriptional on regulation. first predominantly chapter The focuses
The first chapter predominantly focuses on transcriptional regulation.
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by the major in high-throughput thesis is challenges The sequencing analysis. concluded listing
The thesis is concluded by listing the major challenges in high-throughput sequencing analysis.
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discuss I demanding the also questions top data. sequencing of current the integration
I also discuss the current top questions demanding the integration of sequencing data.
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in understanding image holistic provide insight We and deep this into a deblurring review.
We provide a holistic understanding and deep insight into image deblurring in this review.
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years. of has lot the attention a drawn recent identification Biometric-based in
Biometric-based identification has drawn a lot of attention in the recent years.
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Among all features. a rich biometrics, of is known palmprint to possess set
Among all biometrics, palmprint is known to possess a rich set of features.
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result accurate in introduced here identification. near-perfectly The a features
The features introduced here result in a near-perfectly accurate identification.
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of significantly recent large-scale image Image years the in with availability classification sets. advanced has
Image classification has advanced significantly in recent years with the availability of large-scale image sets.
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Attributes the Caltech-UCSD datasets. substantially establish a on and state-of-the-art Animals with Birds improved We
We establish a substantially improved state-of-the-art on the Animals with Attributes and Caltech-UCSD Birds datasets.
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By combining results. improve different output embeddings, we further
By combining different output embeddings, we further improve results.
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cumulative measures interference. to the of used amount quantify We linkage disequilibrium
We used cumulative linkage disequilibrium measures to quantify the amount of interference.
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are by experimental These from data one predictions HIV-infected patient. supported
These predictions are supported by experimental data from one HIV-infected patient.
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Thus, escapes interference explain why later could are slower.
Thus, interference could explain why later escapes are slower.
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experiments well with two Networks very literature. the We known from made Bayesian
We made experiments with two very well known Bayesian Networks from the literature.
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most first we contribute problem. and review In work, comprehensive on this recent the this
In this work, we contribute the first comprehensive and most recent review on this problem.
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interesting by We also these results. to analyzing point some discoveries
We also point to some interesting discoveries by analyzing these results.
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In of spite population the the \emph{Ae. of dynamics
In spite of the population dynamics of the \emph{Ae.
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stability of was and analysis The equilibrium performed.
The analysis of equilibrium and stability was performed.
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follows of climate Cenozoic. evolution evolution the the biodiversity Their
Their biodiversity evolution follows the climate evolution of the Cenozoic.
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Earth is the evolution understand. the of hard Cenozoic climate to considering When processes, only
When considering only Earth processes, the climate evolution of the Cenozoic is hard to understand.
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losses in other conditions. Adaptation and environment often gains fitness to in one results
Adaptation to one environment often results in fitness gains and losses in other conditions.
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developments accessible. becoming more sequencing technologies, in novel data time-sampled and are With available
With novel developments in sequencing technologies, time-sampled data are becoming more available and accessible.
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in these parallel to from datasets. been population Naturally, parameters infer there genetic efforts have
Naturally, there have been efforts in parallel to infer population genetic parameters from these datasets.
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number on sequences. We system of evaluate motion a monocular human the large
We evaluate the system on a large number of monocular human motion sequences.
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to Simulation results used illustrate our are findings.
Simulation results are used to illustrate our findings.
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control of absence in the ground points).
in the absence of ground control points).
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monocular single we a depth from Next, image. estimate key body measurements
Next, we estimate key body measurements from a single monocular depth image.
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squares Levenberg-Marquardt least flexible is algorithm procedure problems. solve The iterative a to used non-linear
The Levenberg-Marquardt algorithm is a flexible iterative procedure used to solve non-linear least squares problems.
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show approach. and stability to efficiency of compositional the this simulated and data Applications real
Applications to real and simulated compositional data show the stability and efficiency of this approach.
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effectiveness demonstrate comparisons and its \emph{state-of-the-art} through a real example. with simulations, We the data
We demonstrate its effectiveness through simulations, comparisons with the \emph{state-of-the-art} and a real data example.
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matrix are based features Textural gray image level extracted of fabric co-occurrence (GLCM). on
Textural features of fabric image are extracted based on gray level co-occurrence matrix (GLCM).
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on output real this The shown time monitor. of implementation a was
The real time output of this implementation was shown on a monitor.
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This dynamics. with a introduces state-space time-varying paper linear model
This paper introduces a linear state-space model with time-varying dynamics.
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Bayesian approximation. The posterior using is inference performed variational
The posterior inference is performed using variational Bayesian approximation.
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years from has In learning attention the machine significant aggregation received recent rank community.
In recent years rank aggregation has received significant attention from the machine learning community.
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study ranking. a known the collaborative as problem version We of
We study a version of the problem known as collaborative ranking.
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The connection a to the standard completion matrix very here interesting have results problem.
The results here have a very interesting connection to the standard matrix completion problem.
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a pulse-based, transfer may is dynamically through Because routed neural circuit. information be
Because transfer is pulse-based, information may be dynamically routed through a neural circuit.
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effective and describe protein temperatures. higher complementary respectively These at of aspects lower activity,
These describe complementary aspects of protein activity, at respectively higher and lower effective temperatures.
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To series the of approximations analysis, CRLBs representations computation introduced. and and are facilitate
To facilitate computation and analysis, series representations and approximations of the CRLBs are introduced.
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previous a in conclusion the This result case. generalizes narrowband
This conclusion generalizes a previous result in the narrowband case.
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of the perceived color to subject be appears with The respect to illumination. different
The perceived color of the subject appears to be different with respect to illumination.
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color also photometric spaces. analyze different invariant We
We also analyze different photometric invariant color spaces.
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(ADMM). using We optimization direction of this problem alternating the multipliers solve method
We solve this optimization problem using the alternating direction method of multipliers (ADMM).
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to require smooth we spectral the in process be sufficiently Instead, domain. the
Instead, we require the process to be sufficiently smooth in the spectral domain.
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related foraging have Animal where self-similar optimal to are trajectories movements been strategies central.
Animal movements have been related to optimal foraging strategies where self-similar trajectories are central.
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approaches. also However, very similar tackled has since with been SLAM monocular
However, monocular SLAM has since also been tackled with very similar approaches.
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limits also to and this scale is However, reconstructions. representation memory-intensive applicability small the
However, this representation is also memory-intensive and limits the applicability to small scale reconstructions.
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for have been limitation. explored avenues Several this overcoming
Several avenues have been explored for overcoming this limitation.
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explicit expression require and attempts unavailable are often recover. difficult which to Previous components,
Previous attempts require explicit expression components, which are often unavailable and difficult to recover.
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than rate. terms positive of in SRC performs C-HiSLR true better even
C-HiSLR performs even better than SRC in terms of true positive rate.
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model an errors. methods fit a shape synthesis minimizing to image by AAM-based texture
AAM-based methods fit a shape model to an image by minimizing texture synthesis errors.
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a image directly facial mapping function Regression-based from points. appearance methods to feature facial learn
Regression-based methods directly learn a mapping function from facial image appearance to facial feature points.
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starvation, the subtilis forms durable spores. To bacterium survive Bacillus
To survive starvation, the bacterium Bacillus subtilis forms durable spores.
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in osmolarity line experiments in medium Indeed, prevents with engulfment predictions. the our decreasing
Indeed, decreasing the medium osmolarity in experiments prevents engulfment in line with our predictions.
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threshold can clustering that is determine needed. empirically an Thus, algorithm
Thus, an algorithm that can empirically determine clustering threshold is needed.
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regions that of the clustering We accuracy. observe repeat presence affects
We observe that the presence of repeat regions affects clustering accuracy.
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does this things Gabora paper. two in
Gabora does two things in this paper.
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Second, it whole views is central evolve. that the world that concept advances she
Second, she advances the central concept that it is whole world views that evolve.
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of is Each her argument convincing. completely section
Each section of her argument is completely convincing.
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is survival. for rapid especially learning, critical Learning,
Learning, especially rapid learning, is critical for survival.
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computer can algebra analyzed. availability of be With games packages, the these
With the availability of computer algebra packages, these games can be analyzed.
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