Results 251 to 260 of about 2,330,920 (308)

Deep generative computed perfusion-deficit mapping of ischaemic stroke. [PDF]

Commun Biol
Tangwiriyasakul C, Borges P, Pombo G, Moriconi S, Elmalem MS, Wright P, Mah YH, Rondina JM, Ourselin S, Nachev P, Cardoso MJ.   +10 more
europepmc   +1 more source

Variational Domain Decomposition For Parallel Image Processing

, 2007
openaire   +1 more source

HiSTaR: identifying spatial domains with hierarchical spatial transcriptomics variational autoencoder. [PDF]

J Transl Med
Yu J, Yuan J, Yi Q, Ye Z, Xu P, Liu W.
europepmc   +1 more source

Introduction to Variational Models in Image Processing

Introduction to Variational Models in Image Processing
openaire  

Some of the next articles are maybe not open access.

Related searches:

Combined First and Second Order Variational Approaches for Image Processing

Jahresbericht der Deutschen Mathematiker-Vereinigung, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
G. Steidl
openaire   +3 more sources

Variational Bayesian image processing on stochastic factor graphs

2008 15th IEEE International Conference on Image Processing, 2008
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represent image patches and their clustering relationship respectively. Unlike previous probabilistic graphical models, we model the structure of FGs by a latent variable, which gives
Xin Li
openaire   +2 more sources

Implementation of high‐order variational models made easy for image processing

Mathematical Methods in the Applied Sciences, 2016
High‐order variational models are powerful methods for image processing and analysis, but they can lead to complicated high‐order nonlinear partial differential equations that are difficult to discretise to solve computationally. In this paper, we present some representative high‐order variational models and provide detailed descretisation of these ...
Lu, Wenqi, Duan, Jinming, Qiu, Zhaowen, Pan, Zhenkuan, Liu, Ryan Wen, Bai, Li   +5 more
openaire   +3 more sources

Variational Single Nighttime Image Haze Removal With a Gray Haze-Line Prior

IEEE Transactions on Image Processing, 2022
Influenced by glowing effects, nighttime haze removal is a challenging ill-posed task. Existing nighttime dehazing methods usually result in glowing artifacts, color shifts, overexposure, and noise amplification. Thus, through statistical and theoretical
Wenhui Wang, Anna Wang, Chen Liu
semanticscholar   +1 more source

A convex variational method for super resolution of SAR image with speckle noise

Signal processing. Image communication, 2021
Super resolution (SR) is an attractive issue in image processing. In the synthetic aperture radar (SAR) image, speckle noise is a crucial problem that is multiplicative.
N. Karimi, M. R. Taban
semanticscholar   +1 more source

Matrix-variate variational auto-encoder with applications to image process

Journal of Visual Communication and Image Representation, 2020
Abstract Variational Auto-Encoder (VAE) is an important probabilistic technology to model 1D vectorial data. However, when applying VAE model to 2D image, vectorization is necessary. Vectorization process may lead to dimension curse and lose valuable spatial information.
Jinghua Li, Huixia Yan, Junbin Gao, Dehui Kong, Lichun Wang, Shaofan Wang, Baocai Yin   +6 more
openaire   +1 more source