Results 101 to 110 of about 19,436 (200)
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
We present techniques for speeding up the test-time evaluation of large convolutional networks, designed for object recognition tasks. These models deliver impressive accuracy but each image evaluation requires millions of floating point operations ...
Bruna, Joan +4 more
core
Cerebral small vessel disease (SVD) may be associated with an increased risk of depressive symptoms. Serum uric acid (SUA), an antioxidant, may be involved in the occurrence and development of depressive symptoms, but the mechanism remains unknown ...
Lei Yu +21 more
doaj +1 more source
Handling the Non-smooth Challenge in Tensor SVD: A Multi-objective Tensor Recovery Framework
Recently, numerous tensor singular value decomposition (t-SVD)-based tensor recovery methods have shown promise in processing visual data, such as color images and videos. However, these methods often suffer from severe performance degradation when confronted with tensor data exhibiting non-smooth changes.
Jingjing Zheng +5 more
openaire +2 more sources
Introduction The INflammation and Small Vessel Disease (INSVD) study aims to investigate whether peripheral inflammation, immune (dys)regulation and blood–brain barrier (BBB) permeability relate to disease progression in cerebral small vessel disease ...
Roy P C Kessels +14 more
doaj +1 more source
Randomized block Krylov method for approximation of truncated tensor SVD
This paper is devoted to studying the application of the block Krylov subspace method for approximation of the truncated tensor SVD (T-SVD). The theoretical results of the proposed randomized approach are presented. Several experimental experiments using synthetics and real-world data are conducted to verify the efficiency and feasibility of the ...
Kooshkghazi, Malihe Nobakht +2 more
openaire +2 more sources
Jacobi-type method for the SVD-like tensor decomposition
For a general third-order tensor A we are looking for its SVD-like decomposition.
openaire +2 more sources
A Hypercomplex Tensor-SVD and Its Application
identifier:oai:t2r2.star.titech.ac.jp ...
openaire
OMT and tensor SVD-based deep learning model for segmentation and predicting genetic markers of glioma: A multicenter study. [PDF]
Zhu Z +23 more
europepmc +1 more source
Two-conformer equilibrium of maltose-binding protein in the absence of ligand from residual dipolar coupling analysis. [PDF]
Shen Y, Bax A.
europepmc +1 more source

