Cleve Moler, Who Unlocked the Power of Computing for Millions, Dies at 86

He built interfaces that allowed engineers, scientists and everyday people to solve difficult problems without having to ...
C&EN

Identifying Balls Feature in a Large-Scale Laser Point Cloud of a Coal Mining Environment by a Multiscale Dynamic Graph Convolution Neural Network

College of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China ...
IEEE

A Dual Convolution Hybrid Multi-Model for Code Vulnerability Detection

Abstract: Existing vulnerability detection models can typically detect only a limited range of vulnerabilities. As the variety of vulnerabilities increases, performance will be reduced. Graph ...
LinkedIn

Convolution vs. Correlation — A Hands-On Dive into Image Filtering with MATLAB

Understanding how machines interpret visual information starts with two fundamental concepts in image processing: convolution and correlation. These techniques are often mentioned in textbooks, but ...
Nature

Uncertainty-driven mixture convolution and transformer network for remote sensing image super-resolution

Recently, convolutional neural networks (CNNs) and Transformer-based Networks have exhibited remarkable prowess in the realm of remote sensing image super-resolution (RSISR), delivering promising ...
GitHub

convolutional-codes

This repository is the MATLAB codes related to the following article: "Hybrid HMM Decoder For Convolutional Codes By Joint Trellis-Like Structure and Channel Prior" ...
Princeton University

ELE 201: Information Signals

Signals that carry information play a central role in technology and engineering — signals ranging from sound and images to sensors, radar, communication, MRI, ultrasound, touch-screens, GPS, and ...
Nature

Deep neural network-based classification of cardiotocograms outperformed conventional algorithms

Cardiotocography records fetal heart rates and their temporal relationship to uterine contractions. To identify high risk fetuses, obstetricians inspect cardiotocograms (CTGs) by eye. Therefore, CTG ...
Frontiers

Using Deep Convolutional Neural Networks for Neonatal Brain Image Segmentation

Deep learning neural networks are especially potent at dealing with structured data, such as images and volumes. Both modified LiviaNET and HyperDense-Net performed well at a prior competition ...