US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.

For decades, cybersecurity relied heavily on signature-based detection and static rule systems. These tools were effective ...

NEW YORK and DAEJEON, South Korea, Dec. 11, 2025 /PRNewswire/ -- Korea Innovation Foundation (INNOPOLIS), currently operating ...

By 2030, agriculture in India could contribute $600 billion to GDP, driven by AI solutions. Sickle Innovations and Dayatani ...

Abstract: Glass manufacturing processes often yield complex defects such as bubbles, stones, and scratches. While machine vision systems powered by deep learning offer effective defect detection, real ...

Technological Advancements: Significant improvements in inspection systems, particularly machine vision (MV) technology, have revolutionized the surface inspection landscape. Advanced cameras, ...

Surface inspection technologies, such as machine vision (MV), enable automated inspection processes, offering reliable analysis results and superior quality control. The integration of automation ...

Deep vertical holes and re-entrant features challenge the best metrology methods.

Discover top US software testing companies offering expert QA, automation, and scalable solutions. Learn how to pick trusted partners and boost quality ...

A global collaboration including Sunwoda, Chery, Nobel laureate M. Stanley Whittingham, Semitronix, the University of ...

Abstract: The increasing adoption of wind turbines as a key component of renewable energy generation necessitates the development of efficient and reliable maintenance strategies to ensure their ...