Breaking tunnel vision, imaging AI lifts fluorescence image restoration accuracy and speed

Recent years have witnessed great advances in applying deep learning to improve fluorescence microscopy imaging. However, enhancing the fidelity of image restoration networks and improving their ...

FireANTs unlocks faster medical image matching, cutting analysis from a week to minutes

Penn Engineers have developed an open-source algorithm that combines the speed of AI with the precision of geometry to ...
India Today

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 support crater dating, navigation planning and future Moon landing missions.
The New York Times

These Tools Say They Can Spot A.I. Fakes. Do They Really Work?

Artificial intelligence detectors are increasingly used to check the veracity of content online. We ran more than 1,000 tests and found several strengths and plenty of weaknesses. By Stuart A.
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 ...
9to5google

How to use Google Gemini’s built-in AI image detection tool

Tides have changed with the Gemini 3 update, bringing Nano Banana Pro image generation to a wider range of users. The images are so realistic that Google provides an extension that detects images with ...
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 ...
Scientific Research Publishing

Driver Drowsiness Detection Based on Eye Blinking Using Convolutional Neural Network Approach ()

This research presents a Driver Drowsiness Detection System (DDDS) that uses a Convolutional Neural Network (CNN) to improve road safety. The system uses a vast dataset of 97,860 images from the ...