Frontiers

Early detection of brain pathologies through deep learning and advanced neuroimaging approaches

Recent advances in the field of medical imaging and computational neuroscience have transformed the landscape of brain pathology detection. The application ...
The Tech Edvocate

How to create neural network

Spread the love“`html Understanding how to create a neural network can be a game-changer in the fields of artificial intelligence and machine learning. As industries increasingly rely on data-driven ...
The Tech Edvocate

How to use Keras

Spread the love“`html Keras has emerged as one of the most popular deep learning libraries in recent years, notable for its simplicity and ease of use. Whether you’re a seasoned data scientist or a ...
MSN on MSN

Move over, NASA, this Jharkhand AI breakthrough could guide future space missions

At BIT Mesra in Ranchi, a three-woman team has trained AI to detect and analyse lunar craters. The ISRO-backed work could ...
Live Science

'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images

Scientists have built a "thermodynamic computer" that can produce images from random disturbances in data, that is, noise. In doing so, they have mimicked the generative artificial intelligence (AI) ...
LinkedIn

Convolutional Neural Network (CNN)

Convolutional Neural Network (CNN) is an advanced version of artificial neural networks (ANNs), primarily designed to extract features from grid-like matrix datasets. This is particularly useful for ...
EurekAlert!

Neural network helps detect gunshots from illegal rainforest poaching

HONOLULU, Dec. 2, 2025 — Wildlife poaching remains a major conservation concern. Technological advancements have enabled webs of acoustic sensors to be deployed throughout rainforests, creating the ...
GitHub

Malware Detection using Deep Learning

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...
Frontiers

A vision-based drowsiness detection system for railway operators using lightweight convolutional neural networks

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...
IEEE

Threshold-Free Event Detection for Nonintrusive Load Monitoring Using Motif Difference Field Images and Convolutional Neural Networks

Abstract: Event detection is a critical process in non-intrusive load monitoring (NILM). Accurate detection enhances subsequent load identification and facilitates a prompt understanding of the system ...
IEEE

Using Convolutional Neural Networks to Detect In-Field PV Module Glass Cracks

Abstract: Double-glass photovoltaic modules are being increasingly deployed, and there is a growing concern about glass cracking in these modules. To confirm this phenomenon, to quantify the rates of ...