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damilojohn
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Text-Descrambling

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acquisition of lower time, i.e. to leads acquired the coefficients amount image Reducing
Reducing the amount of acquired image coefficients leads to lower acquisition time, i.e.
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the MRI exposition of to time apparatus.
time of exposition to the MRI apparatus.
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Face procedure. application detection was above explain chosen to
Face detection application was chosen to explain above procedure.
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method subgraph. multiplier Furthermore, propose to a the U-statistic we confidence bootstrap construct
Furthermore, we propose a U-statistic multiplier bootstrap method to construct the confidence subgraph.
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and include filters feature distributions. of The statistics velocity spatio-temporal histograms
The feature statistics include histograms of spatio-temporal filters and velocity distributions.
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Epistasis a of adaptation. theory the in concept is key
Epistasis is a key concept in the theory of adaptation.
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depend recent Some information approaches theory. on
Some recent approaches depend on information theory.
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can loci misleading. entropy show shared for We that of be pairs considering
We show that considering shared entropy for pairs of loci can be misleading.
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reason is shared entropy epistasis does pair. imply for that The the not
The reason is that shared entropy does not imply epistasis for the pair.
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observation holds order absence epistasis. the in also of true This higher
This observation holds true also in the absence of higher order epistasis.
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interactions pairwise discuss We identifying using a entropy. refined approach for
We discuss a refined approach for identifying pairwise interactions using entropy.
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semantically in challenge. a notoriously first-order logic is Reasoning
Reasoning semantically in first-order logic is notoriously a challenge.
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share means knowledge. Ontologies widely accepted are to
Ontologies are widely accepted means to share knowledge.
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as in central semantic role such segmentation, labelling Pixel-level tasks, a play understanding. image
Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding.
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widely systems. such method One tight is used the frame wavelet representative
One such representative method is the widely used wavelet tight frame systems.
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multi-view we In of paper this consider the face problem detection.
In this paper we consider the problem of multi-view face detection.
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faces fully capture in dozens also models to of all training They require orientations, e.g.
They also require training dozens of models to fully capture faces in all orientations, e.g.
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verbal memory, fluencies reasoning, short-term and speed, processing auditory-verbal assessed. memory, Long-term non-verbal were
Long-term memory, auditory-verbal short-term memory, processing speed, non-verbal reasoning, and verbal fluencies were assessed.
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verbal and effects. For age fluencies, scored musicians different controls displayed than higher
For verbal fluencies, musicians scored higher than controls and displayed different age effects.
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gap. paper The at filling aims the
The paper aims at filling the gap.
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noise repressor cause transcriptional binding. may a RNA repression between competition and Transcriptional by polymerase
Transcriptional repression may cause transcriptional noise by a competition between repressor and RNA polymerase binding.
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In transcriptional particular, also substantial allows promoters give noise. this weak to
In particular, this allows also weak promoters to give substantial transcriptional noise.
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dynamics migration. and Mathematical cell cytoskeleton modeling of
Mathematical modeling of cytoskeleton dynamics and cell migration.
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to scale-based modeling. from multiscale mechanics: Cell single models
Cell mechanics: from single scale-based models to multiscale modeling.
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the causal is method based The constraint algorithm for discovery. PC state-of-the-art
The PC algorithm is the state-of-the-art constraint based method for causal discovery.
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and a range We high dimensional to real-world of our synthetic method apply datasets.
We apply our method to a range of synthetic and real-world high dimensional datasets.
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parallel-PC relationships. inference regulatory for causal inferring into miRNA-mRNA Furthermore, we a integrate method
Furthermore, we integrate parallel-PC into a causal inference method for inferring miRNA-mRNA regulatory relationships.
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observations. of forward to the is admitted explored form model The the likelihoods well
The well admitted forward model is explored to form the likelihoods of the observations.
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leads Sylvester solving Maximizing equation. likelihoods a the to
Maximizing the likelihoods leads to solving a Sylvester equation.
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closed-form Efficient with inference memory footprint. straightforward computations parallelisation a distributed for and small allows
Efficient closed-form inference allows for straightforward parallelisation and distributed computations with a small memory footprint.
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GP resources data can sufficient handle our distributed computing arbitrarily sets. large With model
With sufficient computing resources our distributed GP model can handle arbitrarily large data sets.
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Different situations. required of clusterings different characteristics are in
Different characteristics of clusterings are required in different situations.
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with tractability such fail CSPs most restrictions to global However, guarantee for constraints.
However, most such restrictions fail to guarantee tractability for CSPs with global constraints.
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therefore constraints. instances structural restrictions applicability the with We study of to such
We therefore study the applicability of structural restrictions to instances with such constraints.
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w.r.t. ensemble to of shaped For simultaneously this, policies, an learn propose we
For this, we propose to simultaneously learn an ensemble of policies, shaped w.r.t.
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a scales. many range and heuristics of on
many heuristics and on a range of scales.
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then policy by is obtained voting. The target
The target policy is then obtained by voting.
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shape multi-scale to a sketch-based approach We present retrieval.
We present a multi-scale approach to sketch-based shape retrieval.
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image blocks using connected into The preprocessed input component and segmented analysis. is
The input image is preprocessed and segmented into blocks using connected component analysis.
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block the obtain based morphology the approach. of using segmented skeleton We
We obtain the skeleton of the segmented block using morphology based approach.
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weight is task in an non-trivial, important matching generation however a technique. instance Automatic
Automatic weight generation is a non-trivial, however an important task in instance matching technique.
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Thus solve far, issues. techniques some different proposed have various pressing of the to researchers
Thus far, various researchers have proposed different techniques to solve some of the pressing issues.
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medical segmentation representative image techniques. paper an overview This seminar presents of
This seminar paper presents an overview of representative medical image segmentation techniques.
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The is condition valid. the measurement primary necessary a condition and sufficient that is
The primary condition is the necessary and sufficient condition that a measurement is valid.
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reconstruction We conjecture, when i.e., threshold. impossible of this below half prove one is the
We prove one half of this conjecture, i.e., reconstruction is impossible when below the threshold.
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direction, to weighted In the introduce label the a exploit positive we information. graph
In the positive direction, we introduce a weighted graph to exploit the label information.
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sets paper, advantages. to we use these and this several data In real illustrate simulated
In this paper, we use several simulated and real data sets to illustrate these advantages.
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of We extensions also will model. our some discuss briefly
We will also briefly discuss some extensions of our model.
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of principles Extending perception i.e. the image
Extending the principles of image perception i.e.
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feature a represent interactions central of human all exchanges. Reciprocating
Reciprocating interactions represent a central feature of all human exchanges.
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steps into the future. different of plan Agents may also numbers
Agents may also plan different numbers of steps into the future.
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However, complexities inordinately IPOMDPs challenging. the computationally various make
However, the various complexities make IPOMDPs inordinately computationally challenging.
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elucidate richness of interactive and behaviour use inference. generated We sophistication the to
We use generated behaviour to elucidate the richness and sophistication of interactive inference.
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of evaluation the This complete most correctors collection has so high-performance error far.
This evaluation has the most complete collection of high-performance error correctors so far.
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presented. is in A models for B-splines mixed algorithm fast
A fast algorithm for B-splines in mixed models is presented.
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because sparse. attractive, B-splines have computational and are are support the local corresponding matrices
B-splines have local support and are computational attractive, because the corresponding matrices are sparse.
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in We discovering for approach novel interactions videos. a human present
We present a novel approach for discovering human interactions in videos.
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carried datasets, VIRAT, Activity, been Extensive Collective UT-interaction. experiments three and over out have challenging
Extensive experiments have been carried out over three challenging datasets, Collective Activity, VIRAT, and UT-interaction.
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retrieval. representing We for method for and motion video classification a propose information
We propose a method for representing motion information for video classification and retrieval.
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on datasets. Experimental model achieves state-of-the-arts several simple, our that, results albeit show benchmark results
Experimental results show that, albeit simple, our model achieves state-of-the-arts results on several benchmark datasets.
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segmentation maximum is and principle entropy used images. of The in thresholding largely
The maximum entropy principle is largely used in thresholding and segmentation of images.
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in of Here, entropic index determining discuss role its we the thresholds. the
Here, we discuss the role of its entropic index in determining the thresholds.
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framework. configurable also incorporates solvers, and providing usable It state-of-the-art a
It incorporates state-of-the-art solvers, providing also a usable and configurable framework.
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high-dimension datasets. size Our size traditional and high-sample method low-sample both proposed low-dimensional handles
Our proposed method handles both high-dimension low-sample size and traditional low-dimensional high-sample size datasets.
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conflicting involving a Multicriteria decision a person problem aims analysis decision criteria. at facing supporting
Multicriteria decision analysis aims at supporting a person facing a decision problem involving conflicting criteria.
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the first can be that the general case. show unbounded We length in of explanations
We show first that the length of explanations can be unbounded in the general case.
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include the D-criteria. criteria popular most A- The and
The most popular criteria include the A- and D-criteria.
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from for idea ontologies. an paper generation use presents This learning of rule inductive
This paper presents an idea of inductive learning use for rule generation from ontologies.
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cross-modal we corresponded focus with paper, on partially In this hashing data.
In this paper, we focus on cross-modal hashing with partially corresponded data.
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full correspondence performance. The enhance without hashing to made are in data use the
The data without full correspondence are made in use to enhance the hashing performance.
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experiments With such systems, to those post-stimulus well-timed similar obtained. from be responses can
With such systems, well-timed post-stimulus responses similar to those from experiments can be obtained.
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way. seamless aspects a related) process in
process related) aspects in a seamless way.
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to is the when the challenging video becomes dynamic. used capture problem especially camera The
The problem especially becomes challenging when the camera used to capture the video is dynamic.
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approaches pros/cons, representative motivations, are and strategies, compared. The of and described performance
The motivations, strategies, pros/cons, and performance of representative approaches are described and compared.
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for research promising future are directions Moreover, discussed.
Moreover, promising directions for future research are discussed.
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A the book given is follows. of overview as brief
A brief overview of the book is given as follows.
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meaningful learning users' aims interactions enhance through them. experience It with to providing
It aims to enhance users' learning experience through providing meaningful interactions with them.
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evidence the original conclude there for claim. no We is that
We conclude that there is no evidence for the original claim.
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optimization in black-box expensive of constraints arise problems. many Unknown types
Unknown constraints arise in many types of expensive black-box optimization problems.
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pathologies when to lead can constraints. EI with However, used
However, EI can lead to pathologies when used with constraints.
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approaches suffer failure from not these modes. By do contrast, information-based
By contrast, information-based approaches do not suffer from these failure modes.
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selection annealing estimates AIS problem an is for obtaining of accurate schedule. important the One
One important problem for obtaining accurate AIS estimates is the selection of an annealing schedule.
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belief A of an basic fusion for using assignments information layer approach. combination
A layer for combination of basic belief assignments using an information fusion approach.
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the decision Ranking is to system used making. ultimately decisions support
Ranking the system decisions is ultimately used to support decision making.
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have problems. to Bayesian networks learning neural In approach not does these the principle,
In principle, the Bayesian approach to learning neural networks does not have these problems.
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network to dataset techniques and lack sizes. scalability large existing However, Bayesian
However, existing Bayesian techniques lack scalability to large dataset and network sizes.
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are written For by consistent with each some people multiple other. descriptions images,
For some images, descriptions written by multiple people are consistent with each other.
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images, considerably. But people other for vary descriptions across
But for other images, descriptions across people vary considerably.
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the notion image this paper, In we of introduce specificity.
In this paper, we introduce the notion of image specificity.
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to ecological are communities. to interactions fundamental interspecific thought structures of contribute Dynamic
Dynamic interspecific interactions are thought to contribute to fundamental structures of ecological communities.
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proposed be intransitive is structure. an referred arrangement as that to an such It
It is proposed that such an arrangement be referred to as an intransitive structure.
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Gustafson-Kessel be for clustering. a generalization This algorithm the of considered can algorithm fuzzy
This algorithm can be considered a generalization of the Gustafson-Kessel algorithm for fuzzy clustering.
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algorithm using learning. Segmentation A proposed Fusion distributed is consensus Semi-supervised and
A Semi-supervised Segmentation Fusion algorithm is proposed using consensus and distributed learning.
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a (SSSF). Semi-supervised algorithm USF called Semi-supervision Segmentation using is in new incorporated Fusion
Semi-supervision is incorporated in USF using a new algorithm called Semi-supervised Segmentation Fusion (SSSF).
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a study. in efficiency the is simulation The algorithm illustrated of
The efficiency of the algorithm is illustrated in a simulation study.
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to the pose neural object. use the a of predict (CNN) network convolutional We
We use a convolutional neural network (CNN) to predict the pose of the object.
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pixel using trained normals synthetic containing images rendered objects. CNN is in This
This CNN is trained using pixel normals in images containing rendered synthetic objects.
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it algorithms tested data. on real outperforms real data, When on alternative trained
When tested on real data, it outperforms alternative algorithms trained on real data.
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in the domain. is Image important stage enhancement image-processing an
Image enhancement is an important stage in the image-processing domain.
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image is the The equalization. known enhancement most method histogram
The most known image enhancement method is the histogram equalization.
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