Deep learning high-content imaging is rapidly reshaping image-based screening in the modern laboratory environment. As high-content screening (HCS) generates increasingly large and complex datasets, ...

Researchers at the University of California San Diego and the Allen Institute for AI have built a climate emulator that ...

A squat can look simple until it starts going wrong. Knees drift, backs round, shoulders tighten, and without someone ...

Shifting focus on a visual scene without moving our eyes — think driving, or reading a room for the reaction to your joke — is a behavior known as covert attention. We do it all the time, but little ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Abstract: Convolutional Neural Networks have become a popular image and video recognition tool, achieving state-of-the-art performance in various domains such as object detection, face recognition, ...

Abstract: Conventional optical networks are limited by static operational methods that hinder their scalability and effectiveness. As networks operate with reduced margins to maximize resource ...

ABSTRACT: This research investigates deep learning-based approach for defect detection in the steel production using Severstal steel dataset. The developed system integrates DenseNet121 for ...