Results 51 to 60 of about 28,961 (286)
Improving compressed sensing with the diamond norm
, 2016 In low-rank matrix recovery, one aims to reconstruct a low-rank matrix from a minimal number of linear measurements. Within the paradigm of compressed sensing, this is made computationally efficient by minimizing the nuclear norm as a convex surrogate ...
Eisert, Jens +3 more
core +1 more source
Hyperspectral Image Denoising via Framelet Transformation Based Three-Modal Tensor Nuclear Norm
Remote Sensing, 2021 During the acquisition process, hyperspectral images (HSIs) are inevitably contaminated by mixed noise, which seriously affects the image quality. To improve the image quality, HSI denoising is a critical preprocessing step.
Wenfeng Kong, Yangyang Song, Jing Liu
doaj +1 more source
Efficient tensor completion for color image and video recovery: Low-rank tensor train
, 2016 This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its ...
Bengua, Johann A. +3 more
core +1 more source
, 2018 In tensor completion tasks, the traditional low-rank tensor decomposition models suffer from the laborious model selection problem due to their high model sensitivity.
Cao, Jianting +4 more
core +1 more source
Robust Tensor Factorization for Color Image and Grayscale Video Recovery
IEEE Access, 2020 Low-rank tensor completion (LRTC) plays an important role in many fields, such as machine learning, computer vision, image processing, and mathematical theory.
Shiqiang Du +4 more
doaj +1 more source
Spatiotemporal traffic data imputation via tensorial weighted Schatten‐p norm minimization
IET Intelligent Transport Systems, 2022 Spatiotemporal traffic data exhibit multi‐granular low‐rank structure due to their periodicity among different timelines. Traditional low rank data completion methods fail to characterize such properties and produce unsatisfactory results for data ...
Shaofan Wang +4 more
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 The hyperspectral image (HSI) is easily contaminated by various kinds of mixed noise (such as Gaussian noise, impulse noise, stripes, and deadlines) during the process of data acquisition and conversion, which significantly affect the quality and ...
Pengfei Liu, Lanlan Liu, Liang Xiao
doaj +1 more source
Spectral norm of random tensors [PDF]
, 2014 We show that the spectral norm of a random $n_1\times n_2\times \cdots \times n_K$ tensor (or higher-order array) scales as $O\left(\sqrt{(\sum_{k=1}^{K}n_k)\log(K)}\right)$ under some sub-Gaussian assumption on the entries.
Suzuki, Taiji, Tomioka, Ryota
core
RIPK4 function interferes with melanoma cell adhesion and metastasis
Molecular Oncology, EarlyView.RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski +9 more
wiley +1 more source
Multi-tensor Completion for Estimating Missing Values in Video Data
, 2014 Many tensor-based data completion methods aim to solve image and video in-painting problems. But, all methods were only developed for a single dataset.
Cichocki, Andrzej, Guo, Lili, Li, Chao
core +1 more source