Compression of Deep Neural Networks with Structured Sparse Ternary Coding
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Signal Processing Systems"
DOI: 10.1007/s11265-018-1418-z
Abstract: Deep neural networks (DNNs) contain large number of weights, and usually require many off-chip memory accesses for inference. Weight size compression is a major requirement for on-chip memory based implementation of DNNs, which not only… read more here.
Keywords: compression deep; deep neural; neural networks; networks structured ... See more keywords
Structured Sparse Regularized TSK Fuzzy System for predicting therapeutic peptides
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac135
Abstract: Therapeutic peptides act on the skeletal system, digestive system and blood system, have antibacterial properties and help relieve inflammation. In order to reduce the resource consumption of wet experiments for the identification of therapeutic peptides,… read more here.
Keywords: therapeutic peptides; system; structured sparse; sparse regularized ... See more keywords
Online Structured Sparsity-Based Moving-Object Detection From Satellite Videos
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2020.2976855
Abstract: Inspired by the recent developments in computer vision, low-rank and structured sparse matrix decomposition can be potentially be used for extract moving objects in satellite videos. This set of approaches seeks for rank minimization on… read more here.
Keywords: lsd; low rank; online; satellite videos ... See more keywords
Minimizing the distortions in electrophysiological source imaging of cortical oscillatory activity via Spectral Structured Sparse Bayesian Learning
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2023.978527
Abstract: Oscillatory processes at all spatial scales and on all frequencies underpin brain function. Electrophysiological Source Imaging (ESI) is the data-driven brain imaging modality that provides the inverse solutions to the source processes of the EEG,… read more here.
Keywords: inverse solutions; structured sparse; source; spectral structured ... See more keywords