A high-performance AI framework enhances anomaly detection in industrial systems using optimized Graph Deviation Networks and graph attention mechanisms. Delivering 97% faster detection and improved ...

In this study, we explore an image-based method to automate the manual anomaly detection process on quality control plots using deep learning. To do this we trained a Convolutional Neural Network (CNN ...

Overview: Claude 4 generates accurate, scalable code across multiple languages, turning vague prompts into functional solutions.It detects errors, optimizes per ...

More information: Shiru Wu et al, Point Defect Detection and Classification in MoS2 Scanning Tunneling Microscopy Images: A Deep Learning Approach, Molecules (2025).

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in ...

In order to improve the diagnostic accuracy of deep-learning AI algorithms, models require larger amounts of high-quality training data, which presents a significant burden for pathologists or ...

SMU Assistant Professor Pang Guansong’s research to improve artificial intelligence used in aircraft surface inspections aims to make the skies even safer while reducing aircraft maintenance costs.