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damilojohn
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Text-Descrambling

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features are not easily discriminatory measurable. However,
However, discriminatory features are not easily measurable.
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experimentation is for discriminatory Investigative features. necessary identifying
Investigative experimentation is necessary for identifying discriminatory features.
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measurements, scale and statistical descriptors, contrast structures.
statistical descriptors, contrast measurements, and scale structures.
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we results under configurations. obtain various reasonable This way,
This way, we obtain reasonable results under various configurations.
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unconstrained of setting. albums the We an photo identities in task peoples' in explore recognizing
We explore the task of recognizing peoples' identities in photo albums in an unconstrained setting.
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phenomena Earth's to surface. study the by used acquired are Multispectral satellites on images
Multispectral images acquired by satellites are used to study phenomena on the Earth's surface.
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(MD) Macular field central visual loss. causes degeneration
Macular degeneration (MD) causes central visual field loss.
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with along structures the is associated degeneration pathways. MD of visual
MD is associated with degeneration of structures along the visual pathways.
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morphometry . field degeneration visual voxel-based visual macular Keywords: - - pathway -
Keywords: macular degeneration - visual pathway - visual field - voxel-based morphometry .
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The is former for latter. the usually the basis
The former is usually the basis for the latter.
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hull are numbers. few of in character features convex based recognition handwritten for Experiments
Experiments of convex hull based features for handwritten character recognition are few in numbers.
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are these combined similarity consid-ered of sources information, as measures, establish Perfectible links. to
Perfectible similarity measures, consid-ered as sources of information, are combined to establish these links.
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powerful uncertain is tool for functions belief of a combining such mathematical theory The information.
The theory of belief functions is a powerful mathematical tool for combining such uncertain information.
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for characterizing important trajectory recognition object. Motion moving of an property the is
Motion trajectory recognition is important for characterizing the moving property of an object.
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this trajectories. method paper novel In extraction we for a propose feature
In this paper we propose a novel feature extraction method for trajectories.
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feature trajectory Experimental show the improvement than results shows methods. that, proposed state-of-art encouraging
Experimental results show that, the proposed trajectory feature shows encouraging improvement than state-of-art methods.
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structure the normal a in of cells. change Cancer the with network progresses in gene
Cancer progresses with a change in the structure of the gene network in normal cells.
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way flexible to function a information combine provides provided by Belief sources. different theory
Belief function theory provides a flexible way to combine information provided by different sources.
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Some to help choose hypothesis. the most rules likely
Some rules help to choose the most likely hypothesis.
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made a a of Others set hypotheses. that is on allow decision
Others allow that a decision is made on a set of hypotheses.
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Consequently the speed system true vehicles our and accurately. fast computes of moving
Consequently our system computes the true speed of moving vehicles fast and accurately.
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effective selective proposal We sampling using object propose techniques. two methods
We propose two effective selective sampling methods using object proposal techniques.
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classification. in the how activities terms of decomposed be to
how the activities to be decomposed in terms of classification.
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partially the be activated to is configuration allowed network inference. during
the network configuration is allowed to be partially activated during inference.
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outperforms methods. approach in state-of-the-art Our scenarios, and is challenging validated
Our approach is validated in challenging scenarios, and outperforms state-of-the-art methods.
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large human activity addition. A database videos RGB-D in of is presented
A large human activity database of RGB-D videos is presented in addition.
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on hard cases failed to able before. now are for They they succeed which
They are now able to succeed on hard cases for which they failed before.
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whose scope from algorithm The local steps, three consists global. changes of to
The algorithm consists of three steps, whose scope changes from local to global.
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a local from In it step features of (e.g. images local pair extracts the
In the local step it extracts from a pair of images local features (e.g.
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of order belief the function. develop this will study relation, consonant case In we to
In order to develop this relation, we will study the case of consonant belief function.
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into modularity as We develop study of the how brain changes children human adults.
We study how modularity of the human brain changes as children develop into adults.
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is fitness extracted from model. function A the
A fitness function is extracted from the model.
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exploring suggested. modularity performance are Experiments the on cognitive of effect
Experiments exploring the effect of modularity on cognitive performance are suggested.
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or be biomarker a Modularity disease. for injury, may rehabilitation, potential
Modularity may be a potential biomarker for injury, rehabilitation, or disease.
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systems. become active inattention has very Driver intelligent transportation in assessment a field
Driver inattention assessment has become a very active field in intelligent transportation systems.
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Each relevant information inattention. module driver assessing produces for
Each module produces relevant information for assessing driver inattention.
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well ignorant information. of being own information, their agents' as other maintaining private as
being ignorant of other agents' information, as well as maintaining their own private information.
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for year. multi-scale This one over synthetic on a NC-Florida implemented data-set was
This was implemented on a multi-scale synthetic data-set over NC-Florida for one year.
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it decision nature subtleties of dynamic is menu-dependent regret-minimization The applied to problems. creates when
The menu-dependent nature of regret-minimization creates subtleties when it is applied to dynamic decision problems.
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with more Secondly, to is arise sophistication subtleties inconsistency. dynamic deal used when
Secondly, more subtleties arise when sophistication is used to deal with dynamic inconsistency.
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in role support to computation. modern plays undisputedly vital a GPU) massive implementations CNN
GPU) undisputedly plays a vital role in modern CNN implementations to support massive computation.
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In the to a model process. clean mathematical define paper, framework we this AB-test
In this paper, we define a clean mathematical framework to model the AB-test process.
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interesting sketches of line unique Freehand are representation. visual form an and
Freehand line sketches are an interesting and unique form of visual representation.
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of sketches end process. product Typically, the are such an utilized studied as sketching and
Typically, such sketches are studied and utilized as an end product of the sketching process.
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category-epitomes analyze belonging to and epitome-scores freehand and categories. We object sketches for construct various
We construct and analyze category-epitomes and epitome-scores for freehand sketches belonging to various object categories.
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object Our novel provides for analysis categories. of a the semantic viewpoint nature studying
Our analysis provides a novel viewpoint for studying the semantic nature of object categories.
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decades developed for purpose. been this standard algorithms Throughout have already couple
Throughout couple decades standard algorithms have already been developed for this purpose.
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image algorithms Some these also. to of are applicable degraded
Some of these algorithms are applicable to degraded image also.
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picture, each part. detect we Given for a test hypotheses
Given a test picture, we detect hypotheses for each part.
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resulting function. alternating of apply method minimize We multipliers convex the (ADMM) the direction to
We apply the alternating direction method of multipliers (ADMM) to minimize the resulting convex function.
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of video summaries sharing keyframe-based Compact popular are on video way platforms. a viewership generating
Compact keyframe-based video summaries are a popular way of generating viewership on video sharing platforms.
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associations. is co-regularization to An meaningful used discover subject-scene scheme original
An original co-regularization scheme is used to discover meaningful subject-scene associations.
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The to highly-relevant multimodal resulting keyframes. then select used representations are
The resulting multimodal representations are then used to select highly-relevant keyframes.
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The lead for more even smaller is significant summaries.
The lead is even more significant for smaller summaries.
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developed an also to is objective An iterative minimize and algorithm we constructed function it.
An objective function is constructed and we also developed an iterative algorithm to minimize it.
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based problem. evaluated new bag-of-features is method The image on classification
The new method is evaluated on bag-of-features based image classification problem.
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designed This whose is within candidates algorithm (i.e. vertices graph a are candidacy matching
This algorithm is designed within a candidacy graph whose vertices are matching candidates (i.e.
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of and convergence. for two in a target iterates source parts), pair steps body and
a pair of source and target body parts), and iterates in two steps for convergence.
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(i) relations on It based competitive body partial and matches among compatible possible generates parts.
(i) It generates possible partial matches based on compatible and competitive relations among body parts.
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match of The with SRC. mechanism are optimized the well projections and
The projections are optimized and match well with the mechanism of SRC.
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Therefore, transformed well SRC space. the in performs OP-SRC
Therefore, SRC performs well in the OP-SRC transformed space.
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natural content. problems in and fundamental scene classification are understanding two texture Dynamic video
Dynamic texture and scene classification are two fundamental problems in understanding natural video content.
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a is crucial problems. step these towards Extracting effective robust and solving features
Extracting robust and effective features is a crucial step towards solving these problems.
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term as two-level a Feature We feature ConvNet extraction (TCoF). this Transferred scheme
We term this two-level feature extraction scheme as a Transferred ConvNet Feature (TCoF).
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visual contain often sparse detail. Freehand sketches
Freehand sketches often contain sparse visual detail.
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the However, has images explored. been domain sketch not of
However, the domain of sketch images has not been explored.
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"deep" a paper CNNs. introduces sketch based freehand from recognition on extracted This features framework
This paper introduces a freehand sketch recognition framework based on "deep" features extracted from CNNs.
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is understanding. an Action multimedia problem important in recognition
Action recognition is an important problem in multimedia understanding.
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model. action This an addresses building this by expressive paper compositional problem
This paper addresses this problem by building an expressive compositional action model.
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are domains. between contextual leaf-nodes the and in temporal interactions both Moreover, spatial defined
Moreover, the contextual interactions are defined between leaf-nodes in both spatial and temporal domains.
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production optimization the leaf-nodes associated multi-layer or-nodes) with parameters. the of of with the along
the production of leaf-nodes associated with the or-nodes) along with the optimization of multi-layer parameters.
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information, work In complete cases, under knowledge building bases. agents most complete
In most cases, agents work under complete information, building complete knowledge bases.
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of memory the prohibitive is multi-region limiting requirements. the One adaption segmentation issue large-scale sometimes
One issue limiting the adaption of large-scale multi-region segmentation is the sometimes prohibitive memory requirements.
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instead any This sub-sampling, but method does over all sub-windows. perform optimizes not
This method does not perform any sub-sampling, but instead optimizes over all sub-windows.
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this substantial performance we datasets. available publicly gains on three show approach Using
Using this approach we show substantial performance gains on three publicly available datasets.
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of characterize Information a performance popularity theory tool is gaining to as systems. biological
Information theory is gaining popularity as a tool to characterize performance of biological systems.
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as domain the considered Only entropy are greater than with pool. a domain threshold blocks
Only the domain blocks with entropy greater than a threshold are considered as domain pool.
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significant detection benchmark advances resulted on supervised has Recent datasets. in performance object in salient
Recent advances in supervised salient object detection has resulted in significant performance on benchmark datasets.
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annotations pixel-wise Training however, expensive salient models, of objects. requires such
Training such models, however, requires expensive pixel-wise annotations of salient objects.
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approach. the on our of datasets results Experimental proposed validate benchmark effectiveness
Experimental results on benchmark datasets validate the effectiveness of our proposed approach.
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demonstrate the of variability Furthermore, strong the temporal spread balance and processes. in we spatial
Furthermore, we demonstrate the strong spatial and temporal variability in the balance of spread processes.
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other demic, times more cultural diffusion. more sometimes region and shows at Each
Each region shows sometimes more demic, and at other times more cultural diffusion.
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Only dominance a of areas few, diffusion. environmentally possibly marginal, demic show
Only few, possibly environmentally marginal, areas show a dominance of demic diffusion.
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use such computationally normalising however, of The hampered constant. models intractable by is, a
The use of such models is, however, hampered by a computationally intractable normalising constant.
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fully a discrete treatment makes of parameter Markov This Bayesian difficult. estimation fields random and
This makes parameter estimation and a fully Bayesian treatment of discrete Markov random fields difficult.
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a problem representations effective is understanding. but critical challenging Constructing multimedia in
Constructing effective representations is a critical but challenging problem in multimedia understanding.
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domain features traditional limiting on knowledge, performances rely the often The exiting handcraft of methods.
The traditional handcraft features often rely on domain knowledge, limiting the performances of exiting methods.
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features into manner. a in layer-wise compositional wavelets) Gabor
Gabor wavelets) into compositional features in a layer-wise manner.
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number produce (i.e. a In each base of classifiers layer, we
In each layer, we produce a number of base classifiers (i.e.
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lot of in A research applications. and been many conducted resulted has has
A lot of research has been conducted and has resulted in many applications.
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recent provide a field. We progress this review of in comprehensive to aim the
We aim to provide a comprehensive review of the recent progress in this field.
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addition, evaluation also and we In existing datasets the review influential metrics.
In addition, we also review the existing influential datasets and evaluation metrics.
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design in research segmentation. suggest we directions for image future research and some Finally, flavors
Finally, we suggest some design flavors and research directions for future research in image segmentation.
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structures (e.g. model the This determines iteratively algorithm
This algorithm iteratively determines the model structures (e.g.
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parameter along learning. and the with the their layouts) nodes
the nodes and their layouts) along with the parameter learning.
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variables structures This "switch" by tree hierarchical the introducing model traditional the extends (i.e.
This model extends the traditional hierarchical tree structures by introducing the "switch" variables (i.e.
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variations. that or-nodes) explicitly capture production specify shape to the rules
the or-nodes) that explicitly specify production rules to capture shape variations.
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bricks, sequence At video i.e. the scene, we location of a regular extract of any
At any location of the scene, we extract a sequence of regular video bricks, i.e.
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and spatial temporal over domain. both spanning video volumes
video volumes spanning over both spatial and temporal domain.
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parameter well. empirical studies The analysis and setting as component of are presented
The empirical studies of parameter setting and component analysis are presented as well.
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