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Region-specific Dictionary Learning-based Low-dose Thoracic CT Reconstruction
This paper presents a dictionary learning-based method with region-speci...
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Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images
Computed tomography (CT) has been widely used for medical diagnosis, ass...
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Self-supervised Feature Learning via Exploiting Multi-modal Data for Retinal Disease Diagnosis
The automatic diagnosis of various retinal diseases from fundus images i...
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Multi-Domain Image Completion for Random Missing Input Data
Multi-domain data are widely leveraged in vision applications taking adv...
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A Mean-Field Theory for Learning the Schönberg Measure of Radial Basis Functions
We develop and analyze a projected particle Langevin optimization method...
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Atlas Based Segmentations via Semi-Supervised Diffeomorphic Registrations
Purpose: Segmentation of organs-at-risk (OARs) is a bottleneck in curren...
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Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications
In recent years, significant progress has been made in developing more a...
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Modified U-Net (mU-Net) with Incorporation of Object-Dependent High Level Features for Improved Liver and Liver-Tumor Segmentation in CT Images
Segmentation of livers and liver tumors is one of the most important ste...
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A Mean-Field Theory for Kernel Alignment with Random Features in Generative Adversarial Networks
We propose a novel supervised learning method to optimize the kernel in ...
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On Sample Complexity of Projection-Free Primal-Dual Methods for Learning Mixture Policies in Markov Decision Processes
We study the problem of learning policy of an infinite-horizon, discount...
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Multiple Kernel Learning from U-Statistics of Empirical Measures in the Feature Space
We propose a novel data-driven method to learn multiple kernels in kerne...
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Quantized Minimum Error Entropy Criterion
Comparing with traditional learning criteria, such as mean square error ...
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Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
Magnetic resonance image (MRI) reconstruction is a severely ill-posed li...
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Robustness of Maximum Correntropy Estimation Against Large Outliers
The maximum correntropy criterion (MCC) has recently been successfully a...
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Robust Learning with Kernel Mean p-Power Error Loss
Correntropy is a second order statistical measure in kernel space, which...
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Kernel Risk-Sensitive Loss: Definition, Properties and Application to Robust Adaptive Filtering
Nonlinear similarity measures defined in kernel space, such as correntro...
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Generalized Correntropy for Robust Adaptive Filtering
As a robust nonlinear similarity measure in kernel space, correntropy ha...
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