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basic as the adopted U-Net structure. is DCNN
U-Net is adopted as the basic DCNN structure.
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detailed feature show subdivision of results i.e. the The that map,
The results show that detailed subdivision of the feature map, i.e.
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IN, group number a with achieves accuracy. higher GN or large
GN with a large group number or IN, achieves higher accuracy.
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This improvement mainly generalization. better from comes accuracy model
This accuracy improvement mainly comes from better model generalization.
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are uploaded at maintained Codes and Zhou's Github. Xiao-Yun
Codes are uploaded and maintained at Xiao-Yun Zhou's Github.
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modeling these long-term improve innovations demonstrate results Our the that trajectories. motion of
Our results demonstrate that these innovations improve the modeling of long-term motion trajectories.
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show predict connections recurrent small i.e. skip to the objects, ability occluded Novel
Novel recurrent skip connections show the ability to predict small occluded objects, i.e.
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previous Experiments improvements a our also Carlo network, to quantify literature. and Monte approach,
Experiments also quantify improvements to our previous network, a Monte Carlo approach, and literature.
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divergence introduce to Kullback-Leibler reject on a also We doubtful criterion based examples.
We also introduce a criterion based on Kullback-Leibler divergence to reject doubtful examples.
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is effect visual experiments and performed Extensive included. discussion on enhancement are
Extensive experiments are performed and discussion on visual effect enhancement is included.
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segmentation and training optimised with post-process. a for present lesion ensemble method We method two-stage
We present a two-stage method for lesion segmentation with optimised training method and ensemble post-process.
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sign microcalcifications of cancer. an be breast early of can Cluster
Cluster of microcalcifications can be an early sign of breast cancer.
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data. focus We on estimating video the frequency of human problem from hand-tremor input RGB
We focus on the problem of estimating human hand-tremor frequency from input RGB video data.
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The rate e.g. assumed in constant model,
The constant rate model, assumed in e.g.
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Saleh-Valenzuela to same the reproduce is unable model, effects. the
the Saleh-Valenzuela model, is unable to reproduce the same effects.
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datasets and algorithms. survey state-of-the-art associated This the also public reviews
This survey also reviews the public datasets and associated state-of-the-art algorithms.
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convergence. processes The performed are iteratively until
The processes are performed iteratively until convergence.
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component distance unary employ Specifically, we to the the build geodesic term.
Specifically, we employ the geodesic distance component to build the unary term.
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the outliers. register aim we images step different patients, to yields matching As many of
As we aim to register images of different patients, the matching step yields many outliers.
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algorithm we new which efficiently discards EM-weighting Then a outliers. propose
Then we propose a new EM-weighting algorithm which efficiently discards outliers.
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carried optimization descent Global a with algorithm. fast gradient is out
Global optimization is carried out with a fast gradient descent algorithm.
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register approach large to our allows datasets. robustly This
This allows our approach to robustly register large datasets.
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in and role an pedestrians) cyclists will play future important traffic.
cyclists and pedestrians) will play an important role in future traffic.
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of movement consists detection prediction, The primitive basic e.g. intention
The intention detection consists of basic movement primitive prediction, e.g.
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trajectory. a turning, and future forecast moving, standing, the of
standing, moving, turning, and a forecast of the future trajectory.
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open Heterogeneous, agents and of sets vehicles, infrastructure, interacting (cooperating e.g.
Heterogeneous, open sets of agents (cooperating and interacting vehicles, infrastructure, e.g.
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are inconsistencies resolved the of implausibilities Concealments, intelligence cooperating by collective and agents.
Concealments, implausibilities and inconsistencies are resolved by the collective intelligence of cooperating agents.
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obtained compared. both the Results are approaches using
Results obtained using both the approaches are compared.
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identification. signal limitation based MUSIC, the methods on as for subspace known is This otherwise
This is the limitation for methods based on MUSIC, otherwise known as signal subspace identification.
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appearance. from structure structure-from-motion not actually learns and context This motion, from algorithm only
This algorithm actually learns structure-from-motion from motion, and not only structure from context appearance.
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use videos, moving stabilized camera and Two ones. cases considered, are unstabilized
Two use cases are considered, unstabilized moving camera videos, and stabilized ones.
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their negate drop-out online which effectiveness. cost high However, suffers from treatment might rates,
However, online treatment suffers from high drop-out rates, which might negate their cost effectiveness.
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varying The camera illumination shown changes. improvements and perspective significant have experimental results presented with
The presented experimental results have shown significant improvements with varying illumination and camera perspective changes.
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some drawbacks, i.e. with compact algorithms However, come also
However, compact algorithms also come with some drawbacks, i.e.
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and they to performance problems. tend on premature non-separable poorer show convergence
they tend to premature convergence and show poorer performance on non-separable problems.
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Gaussian modeled a The are and time-variant using unknown values safety spatio-temporal process.
The unknown and time-variant safety values are modeled using a spatio-temporal Gaussian process.
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Many that and complex plants harbor mechanisms transfer. pollen promote outcrossing efficient
Many plants harbor complex mechanisms that promote outcrossing and efficient pollen transfer.
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(SI) self-incompatibility mechanisms, systems. floral include such genetic These adaptations molecular as as well as
These include floral adaptations as well as genetic mechanisms, such as molecular self-incompatibility (SI) systems.
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with association been repeatedly in self-fertilization to lost, has SI (selfing). transitions often Conversely,
Conversely, SI has repeatedly been lost, often in association with transitions to self-fertilization (selfing).
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complexity, of improve lower performance To the is its convolution a target adopted. dilated with
To improve its performance with a target of lower complexity, the dilated convolution is adopted.
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cost. and computational thinner A the to shallower structure is designed decrease
A shallower and thinner structure is designed to decrease the computational cost.
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shows results on scenes. captured promising system road the Our
Our system shows promising results on the captured road scenes.
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of experts method variable selection frameworks A for in proposed. mixture is implicit
A method for implicit variable selection in mixture of experts frameworks is proposed.
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prior We information set covariates. taken where introduce independent of from structure is a a
We introduce a prior structure where information is taken from a set of independent covariates.
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Robust membership a are prior. normal predictors identified gamma using class
Robust class membership predictors are identified using a normal gamma prior.
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implementation inference the a out Fully of Gibbs is via carried sampler. Bayesian
Fully Bayesian inference is carried out via the implementation of a Gibbs sampler.
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one in described as cell were populations Chondrocytes literature. cartilage most
Chondrocytes were described as one cell populations in most cartilage literature.
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training, projections network for and mappings, natural introduced. Bases, Neural are metrics,
Bases, mappings, projections and metrics, natural for Neural network training, are introduced.
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relatively in emerges, simple even naturally datasets. Non-Gaussianity
Non-Gaussianity naturally emerges, even in relatively simple datasets.
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analyzed, of point are Training view. statistics, physics energies from hierarchies and
Training statistics, hierarchies and energies are analyzed, from physics point of view.
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Duality (for observations and between observables pixels) established. example, is
Duality between observables (for example, pixels) and observations is established.
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numerical between and exact studied. solutions is Relationship
Relationship between exact and numerical solutions is studied.
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offered. of financial key a and mathematics problem are interpretations Physics
Physics and financial mathematics interpretations of a key problem are offered.
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is not practical majority for vast Unfortunately, researchers. approach this of the
Unfortunately, this approach is not practical for the vast majority of researchers.
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semantic years. learning progress has great deep shown recent for in segmentation Concurrently,
Concurrently, deep learning for semantic segmentation has shown great progress in recent years.
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tasks in we are propose Specifically, network structure two a these which coupled. highly
Specifically, we propose a network structure in which these two tasks are highly coupled.
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two-stage One the refinement of process. key this is novelty approach
One key novelty of this approach is the two-stage refinement process.
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from paper a modeling that This can head the problem is solve. we proposes Internet
This paper proposes that head modeling from the Internet is a problem we can solve.
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head. target the rough We of shape of reconstruction the
We target reconstruction of the rough shape of the head.
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algorithm. call We boundary-value method our growing
We call our method boundary-value growing algorithm.
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presented. photos downloaded of celebrities Results are the on from Internet
Results on photos of celebrities downloaded from the Internet are presented.
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networks the dynamics spiking of neurons. collective structured of densely connected We analyze hierarchically
We analyze the collective dynamics of hierarchically structured networks of densely connected spiking neurons.
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scenes UAV data. on try We synthetic and real our algorithm both flight
We try our algorithm on both synthetic scenes and real UAV flight data.
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more this is thoroughly. that with a article video our results Along present
Along with this article is a video that present our results more thoroughly.
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problem. classification plays information supervised Label in image an important role hyperspectral
Label information plays an important role in supervised hyperspectral image classification problem.
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be majority vote propagated algorithm. a can the by final calculated label Therefore,
Therefore, the final propagated label can be calculated by a majority vote algorithm.
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also The subtlety discussed. of is interpreting results
The subtlety of interpreting results is also discussed.
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efficiently. And such them exist, if how inputs find to
And if such inputs exist, how to find them efficiently.
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practically use these also by the to implementations. providing We show corresponding solutions, how
We also show how to practically use these solutions, by providing the corresponding implementations.
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capabilities All utilization of medicine. are the invasive in of use minimally these
All these capabilities are of use in the utilization of minimally invasive medicine.
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Micro-Dictionary a In Coding Learning and paper, Deep Network propose we this (DDLCN). novel
In this paper, we propose a novel Deep Micro-Dictionary Learning and Coding Network (DDLCN).
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most has standard deep (pooling, the layers DDLCN connected, learning fully, etc.) input/output, of
DDLCN has most of the standard deep learning layers (pooling, fully, connected, input/output, etc.)
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input an for learning over-complete the dictionary training dictionary data. layer The learns
The dictionary learning layer learns an over-complete dictionary for the input training data.
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several proposed methods learning and learning the with deep We architectures. empirically DDLCN compare dictionary
We empirically compare the proposed DDLCN with several dictionary learning methods and deep learning architectures.
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understanding works. of how bootstrap provides It intuitive an the
It provides an intuitive understanding of how the bootstrap works.
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in details are Mathematical references cited. that available are
Mathematical details are available in references that are cited.
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holds. distributional findings our Our similarity that hypothesis indicate
Our findings indicate that our distributional similarity hypothesis holds.
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domain However, in of received techniques attention only computer maritime recently. vision application
However, application of computer vision techniques in maritime domain received attention only recently.
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challenges. requirements own maritime offers and unique environment its The
The maritime environment offers its own unique requirements and challenges.
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in need Assessment is detections computer of a quality of the vision. fundamental
Assessment of the quality of detections is a fundamental need in computer vision.
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computer defining the vision. of discuss We suitable problem assessment maritime for metrics
We discuss the problem of defining assessment metrics suitable for maritime computer vision.
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consider computer metrics maritime for metrics new proximity vision. bottom assessment edge We as
We consider new bottom edge proximity metrics as assessment metrics for maritime computer vision.
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ESS paper not the MCMC use does for of algorithms. This cover
This paper does not cover the use of ESS for MCMC algorithms.
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local commonly a Existing of matching a global compositions pipelines stage. stage and reassembly consist
Existing reassembly pipelines commonly consist of a local matching stage and a global compositions stage.
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time-critical a multi-object applications. tracking in problem video Online is analysis fundamental
Online multi-object tracking is a fundamental problem in time-critical video analysis applications.
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qualitatively the The algorithm. and experiments conducted the effectiveness quantitatively of demonstrate
The experiments conducted quantitatively and qualitatively demonstrate the effectiveness of the algorithm.
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depth propose We a fully architecture network. end-to-end an convolutional with for also inference
We also propose an architecture for end-to-end depth inference with a fully convolutional network.
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This be security to is potential issue. phenomenon a considered
This phenomenon is considered to be a potential security issue.
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unknown. shared harmful characteristics perturbations such However, of the remain the directions of
However, the characteristics of the shared directions of such harmful perturbations remain unknown.
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stage architecture. structure recurrent-auto to encoder We RNN with the cascade form decoder a a
We cascade the RNN structure with a decoder stage to form a recurrent-auto encoder architecture.
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is the backpropagation. regarding during prior waveform Moreover, information and structure incorporated initialization
Moreover, prior information regarding the waveform structure is incorporated during initialization and backpropagation.
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under robustness the desiderata a the Relevance addition of concern irrelevant consequence information. of relation
Relevance desiderata concern the robustness of a consequence relation under the addition of irrelevant information.
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of semantic to (ir)relevance syntactic what considerations. and amounts For we use account an
For an account of what (ir)relevance amounts to we use syntactic and semantic considerations.
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known non-monotonic criteria relevance are semantic logic. Some from
Some semantic relevance criteria are known from non-monotonic logic.
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investigate of relevance paper warrant properties this structured that In we argumentation desiderata. systems
In this paper we investigate properties of structured argumentation systems that warrant relevance desiderata.
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recently success single-image super-resolution great achieved (SISR). Convolutional have neural networks (CNNs) in
Convolutional neural networks (CNNs) have recently achieved great success in single-image super-resolution (SISR).
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textural tend produce details. these miss and outputs over-smoothed some However, to methods
However, these methods tend to produce over-smoothed outputs and miss some textural details.
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applied Learning impressive to this successfully been results. Deep achieved problem and methods have have
Deep Learning methods have been successfully applied to this problem and have achieved impressive results.
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amount labeled of data. require However, methods large training a these
However, these methods require a large amount of labeled training data.
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Each group adversarial realistic through images is generate used to training. then
Each group is then used to generate realistic images through adversarial training.
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