Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...

Akshay Jagadeesh, an Indian-origin neuroscientist, has joined OpenAI as a research resident after nearly a decade of brain research at Stanford University and Harvard Medical School. With academic ...

A team at the University of Florida has developed a new kind of computer chip that uses light with electricity to perform one ...

This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...

Summary: Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks. Unlike traditional methods that only cluster nodes, this approach groups ...

School of Electronics Engineering (SENSE), Vellore Institute of Technology, Chennai, India Introduction: In recent years, Deep Learning (DL) architectures such as Convolutional Neural Network (CNN) ...

College of Integrated Circuits and Micro-Nano Electronics, School of Microelectronics, State Key Laboratory of Integrated Chip and System, Fudan University, Shanghai 200433, China ...

Introduction: Segmentation of echocardiograms plays a crucial role in clinical diagnosis. Beyond accuracy, a major challenge of video echocardiogram analysis is the temporal consistency of consecutive ...

Abstract: We propose a one-dimensional (1D) Convolutional Neural Network (CNN)-based method for recognizing human activity using triaxial accelerometer data collected from users' smartphones. The ...