Results 41 to 50 of about 522,381 (263)

Multiple feature-enhanced SAR imaging using sparsity in combined dictionaries [PDF]

open access: yes, 2012
Nonquadratic regularization-based image formation is a recently proposed framework for feature-enhanced radar imaging. Specific image formation techniques in this framework have so far focused on enhancing one type of feature, such as strong point ...
Cetin, Mujdat   +3 more
core   +2 more sources

A First Step to Convolutive Sparse Representation

open access: yes, 2008
In this paper an extension of the sparse decomposition problem is considered and an algorithm for solving it is presented. In this extension, it is known that one of the shifted versions of a signal s (not necessarily the original signal itself) has a ...
Babaie-Zadeh, Massoud   +3 more
core   +2 more sources

Visual Tracking Based on Extreme Learning Machine and Sparse Representation

open access: yesSensors, 2015
The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging ...
Baoxian Wang   +4 more
doaj   +1 more source

Saliency Detection Using Sparse and Nonlinear Feature Representation

open access: yesThe Scientific World Journal, 2014
An important aspect of visual saliency detection is how features that form an input image are represented. A popular theory supports sparse feature representation, an image being represented with a basis dictionary having sparse weighting coefficient ...
Shahzad Anwar   +3 more
doaj   +1 more source

Integrated Sparse Coding With Graph Learning for Robust Data Representation

open access: yesIEEE Access, 2020
Sparse coding is a popular technique for achieving compact data representation and has been used in many applications. However, the instability issue often causes degeneration in practice and thus attracts a lot of studies.
Yupei Zhang, Shuhui Liu
doaj   +1 more source

Learning Joint Intensity-Depth Sparse Representations [PDF]

open access: yesIEEE Transactions on Image Processing, 2014
This paper presents a method for learning overcomplete dictionaries composed of two modalities that describe a 3D scene: image intensity and scene depth. We propose a novel Joint Basis Pursuit (JBP) algorithm that finds related sparse features in two modalities using conic programming and integrate it into a two-step dictionary learning algorithm.
Tošić, Ivana, Drewes, Sarah
openaire   +4 more sources

Mechanisms of parasite‐mediated disruption of brain vessels

open access: yesFEBS Letters, EarlyView.
Parasites can affect the blood vessels of the brain, often causing serious neurological problems. This review explains how different parasites interact with and disrupt these vessels, what this means for brain health, and why these processes matter. Understanding these mechanisms may help us develop better ways to prevent or treat brain infections in ...
Leonor Loira   +3 more
wiley   +1 more source

Hyperspectral Image Denoising via Nonlocal Spectral Sparse Subspace Representation

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Hyperspectral image (HSI) denoising based on nonlocal subspace representation has attracted a lot of attention recently. However, most of the existing works mainly focus on refining the representation coefficient images (RCIs) using certain nonlocal ...
Hailin Wang   +5 more
doaj   +1 more source

Image Deblurring and Super-resolution by Adaptive Sparse Domain Selection and Adaptive Regularization

open access: yes, 2010
As a powerful statistical image modeling technique, sparse representation has been successfully used in various image restoration applications. The success of sparse representation owes to the development of l1-norm optimization techniques, and the fact ...
Dong, Weisheng   +3 more
core   +1 more source

Investigating the cell of origin and novel molecular targets in Merkel cell carcinoma: a historic misnomer

open access: yesMolecular Oncology, EarlyView.
This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian   +10 more
wiley   +1 more source

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