Results 41 to 50 of about 2,330,920 (308)
Latent Variable Model for Multi-modal Translation [PDF]
, 2019 In this work, we propose to model the interaction between visual and textual features for multi-modal neural machine translation (MMT) through a latent variable model. This latent variable can be seen as a multi-modal stochastic embedding of an image and
Aziz, Wilker +2 more
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Variational inference for medical image segmentation [PDF]
, 2016 Variational inference techniques are powerful methods for learning probabilistic models and provide significant advantages over maximum likelihood (ML) or maximum a posteriori (MAP) approaches.
Ashburner, J, Blaiotta, C, Cardoso, MJ
core +1 more source
A new image deconvolution method with fractional regularisation
Journal of Algorithms & Computational Technology, 2016 Image deconvolution is an important pre-processing step in image analysis which may be combined with denoising, also an important image restoration technique, and prepares the image to facilitate diagnosis in the case of medical images and further ...
Bryan M Williams +2 more
doaj +1 more source
Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design
Sensors, 2023 In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction. The combination of VAE and various machine learning frameworks has also worked effectively in different ...
Hugo Wai Leung Mak +2 more
doaj +1 more source
Functional Liftings of Vectorial Variational Problems with Laplacian Regularization
, 2019 We propose a functional lifting-based convex relaxation of variational problems with Laplacian-based second-order regularization. The approach rests on ideas from the calibration method as well as from sublabel-accurate continuous multilabeling ...
A Chambolle +15 more
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Power mean based image segmentation in the presence of noise
Scientific Reports, 2022 In image segmentation and in general in image processing, noise and outliers distort contained information posing in this way a great challenge for accurate image segmentation results.
Afzal Rahman +7 more
doaj +1 more source
On convergent finite difference schemes for variational–PDE-based image processing [PDF]
Computational and Applied Mathematics, 2017 We study an adaptive anisotropic Huber functional based image restoration scheme. By using a combination of L2-L1 regularization functions, an adaptive Huber functional based energy minimization model provides denoising with edge preservation in noisy digital images.
V. B. Surya Prasath, Juan C. Moreno
openaire +3 more sources
Global Variational Method for Fingerprint Segmentation by Three-part Decomposition
, 2015 Verifying an identity claim by fingerprint recognition is a commonplace experience for millions of people in their daily life, e.g. for unlocking a tablet computer or smartphone.
Gottschlich, Carsten, Thai, Duy Hoang
core +1 more source
Decomposition of Optical Flow on the Sphere [PDF]
, 2014 We propose a number of variational regularisation methods for the estimation and decomposition of motion fields on the $2$-sphere. While motion estimation is based on the optical flow equation, the presented decomposition models are motivated by recent ...
Kirisits, Clemens +2 more
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Image Processing Variations with Analytic Kernels
, 2012 Let $f\in L^1(\R^d)$ be real. The Rudin-Osher-Fatemi model is to minimize $\|u\|_{\dot{BV}}+ \|f-u\|_{L^2}^2$, in which one thinks of $f$ as a given image, $ > 0$ as a "tuning parameter", $u$ as an optimal "cartoon" approximation to $f$, and $f-u$ as "noise" or "texture". Here we study variations of the R-O-F model having the form $\inf_u\{\|u\|_{\
Garnett, John B. +2 more
openaire +2 more sources