In an environment defined by labor shortages, rising uptime expectations and pressure to improve overall equipment effectiveness (OEE), simple data collection is no longer enough.

Sand has a memory of sorts. Press into a loose pile of dry grains and something moves, not just where your finger sits, but ...

Abstract: The aim of this research is to improve accuracy and efficiency with regard to product defect detection using a deep learning based hybrid model. It combines preprocessing, segmentation, ...

Abstract: Nowadays, with the development of technology, the use of drones has increased in different areas. It is used effectively in many areas, especially defense, shopping, exploration, photography ...

Android Malware Detected Using Machine Learning to Automatically Detect and Click on Ads The malware can switch to a signalling mode that allows attackers to manually scroll and tap through a live ...

Amirali Aghazadeh receives funding from Georgia Tech. When NASA scientists opened the sample return canister from the OSIRIS-REx asteroid sample mission in late 2023, they found something astonishing.

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 ...

ABSTRACT: Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...