Electrical Engineering and Systems Science

All posts under tag "Electrical Engineering and Systems Science"

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Low Barrier Nanomagnet Design for Binary Stochastic Neurons: Design Challenges for Real Nanomagnets with Fabrication Defects

Low Barrier Nanomagnet Design for Binary Stochastic Neurons: Design Challenges for Real Nanomagnets with Fabrication Defects

Much attention has been focused on the design of low barrier nanomagnets (LBM), whose magnetizations vary randomly in time owing to thermal noise, for use in binary stochastic neurons (BSN) which are hardware accelerators for machine learning. The performance of BSNs depend on two important paramete

Computer Science Condensed Matter Systems and Control Electrical Engineering and Systems Science
Self-Adaptive 2D-3D Ensemble of Fully Convolutional Networks for Medical Image Segmentation

Self-Adaptive 2D-3D Ensemble of Fully Convolutional Networks for Medical Image Segmentation

Segmentation is a critical step in medical image analysis. Fully Convolutional Networks (FCNs) have emerged as powerful segmentation models achieving state-of-the-art results in various medical image datasets. Network architectures are usually designed manually for a specific segmentation task so ap

Computer Vision Computer Science Network Image Processing Electrical Engineering and Systems Science
Self-attention based BiLSTM-CNN classifier for the prediction of ischemic and non-ischemic cardiomyopathy

Self-attention based BiLSTM-CNN classifier for the prediction of ischemic and non-ischemic cardiomyopathy

Heart Failure is a major component of healthcare expenditure and a leading cause of mortality worldwide. Despite higher inter-rater variability, endomyocardial biopsy (EMB) is still regarded as the standard technique, used to identify the cause (e.g. ischemic or non-ischemic cardiomyopathy, coronary

Computer Vision Computer Science Machine Learning Image Processing Electrical Engineering and Systems Science
Detection and classification of masses in mammographic images in a multi-kernel approach

Detection and classification of masses in mammographic images in a multi-kernel approach

According to the World Health Organization, breast cancer is the main cause of cancer death among adult women in the world. Although breast cancer occurs indiscriminately in countries with several degrees of social and economic development, among developing and underdevelopment countries mortality r

Computer Vision Computer Science Image Processing Neural Computing Detection Electrical Engineering and Systems Science
From Brain Imaging to Graph Analysis: a study on ADNIs patient cohort

From Brain Imaging to Graph Analysis: a study on ADNIs patient cohort

In this paper, we studied the association between the change of structural brain volumes to the potential development of Alzheimer's disease (AD). Using a simple abstraction technique, we converted regional cortical and subcortical volume differences over two time points for each study subject into

Computer Science Electrical Engineering and Systems Science Analysis Quantitative Biology Image Processing Information Retrieval
Known-plaintext attack and ciphertext-only attack for encrypted single-pixel imaging

Known-plaintext attack and ciphertext-only attack for encrypted single-pixel imaging

In many previous works, a single-pixel imaging (SPI) system is constructed as an optical image encryption system. Unauthorized users are not able to reconstruct the plaintext image from the ciphertext intensity sequence without knowing the illumination pattern key. However, little cryptanalysis abou

Computer Vision Computer Science Cryptography and Security Image Processing Electrical Engineering and Systems Science
StrokeSave: A Novel, High-Performance Mobile Application for Stroke Diagnosis using Deep Learning and Computer Vision

StrokeSave: A Novel, High-Performance Mobile Application for Stroke Diagnosis using Deep Learning and Computer Vision

According to the WHO, Cerebrovascular Stroke, or CS, is the second largest cause of death worldwide. Current diagnosis of CS relies on labor and cost intensive neuroimaging techniques, unsuitable for areas with inadequate access to quality medical facilities. Thus, there is a great need for an effic

Computer Vision Computer Science Machine Learning Learning Statistics Image Processing Electrical Engineering and Systems Science
Towards the 1G of Mobile Power Network: RF, Signal and System Designs to Make Smart Objects Autonomous

Towards the 1G of Mobile Power Network: RF, Signal and System Designs to Make Smart Objects Autonomous

This article reviews some recent promising approaches to make mobile power closer to reality. In contrast with articles commonly published by the microwave community and the communication/signal processing community that separately emphasize RF, circuit and antenna solutions for WPT on one hand and

Computer Science Mathematics Network Information Theory System Electrical Engineering and Systems Science
An Internal Clock Based Space-time Neural Network for Motion Speed Recognition

An Internal Clock Based Space-time Neural Network for Motion Speed Recognition

In this work we present a novel internal clock based space-time neural network for motion speed recognition. The developed system has a spike train encoder, a Spiking Neural Network (SNN) with internal clocking behaviors, a pattern transformation block and a Network Dynamic Dependent Plasticity (NDD

Computer Vision Computer Science Network Image Processing Neural Computing Electrical Engineering and Systems Science

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240
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