Hardware implementation of RRAM based binarized neural networks
Sign Up to like & getrecommendations! Published in 2019 at "APL Materials"
DOI: 10.1063/1.5116863
Abstract: Resistive switching random access memory (RRAM) has been explored to accelerate the computation of neural networks. RRAM with linear conductance modulation is usually required for the efficient weight updating during the online training according to… read more here.
Keywords: online training; neural networks; binarized neural; weight updating ... See more keywords
A Binarized Neural Network Approach to Accelerate in-Vehicle Network Intrusion Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3208091
Abstract: Controller Area Network (CAN) is the de facto standard for in-vehicle networks. However, it is inherently vulnerable to various attacks due to the lack of security features. Intrusion detection systems (IDSs) are considered effective approaches… read more here.
Keywords: intrusion detection; neural network; network; binarized neural ... See more keywords
Reconfigurable Smart In-Memory Computing Platform Supporting Logic and Binarized Neural Networks for Low-Power Edge Devices
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Journal on Emerging and Selected Topics in Circuits and Systems"
DOI: 10.1109/jetcas.2020.3030542
Abstract: Edge computing has been shown to be a promising solution that could relax the burden imposed onto the network infrastructure by the increasing amount of data produced by smart devices. However, reconfigurable ultra-low power computing… read more here.
Keywords: memory computing; memory; neural networks; binarized neural ... See more keywords
Toward Accurate Binarized Neural Networks With Sparsity for Mobile Application.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3173498
Abstract: While binarized neural networks (BNNs) have attracted great interest, popular approaches proposed so far mainly exploit the symmetric sign function for feature binarization, i.e., to binarize activations into -1 and +1 with a fixed threshold… read more here.
Keywords: neural networks; binarized neural; networks sparsity; toward accurate ... See more keywords
PresB-Net: parametric binarized neural network with learnable activations and shuffled grouped convolution
Sign Up to like & getrecommendations! Published in 2022 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.842
Abstract: In this study, we present a novel performance-enhancing binarized neural network model called PresB-Net: Parametric Binarized Neural Network. A binarized neural network (BNN) model can achieve fast output computation with low hardware costs by using… read more here.
Keywords: neural network; bnn; shuffled grouped; presb net ... See more keywords