In modern stone fabrications and precision manufacturing facilities, the sound of production is the ultimate indicator of profitability. When a heavy stone slab is loaded onto a cutting bed, operators ...

Lattice Semiconductor (NASDAQ: LSCC), the low power programmable leader, today announced that its Lattice sensAI™ solution stack was named "AI Edge Solution of the Year" by the 2026 AI Breakthrough ...

description [CVPR 2026][目标检测][开放集缺陷检测] 本文提出 UniSpector 开放集工业缺陷检测框架，通过频域-空域双域特征融合（SSPE ...

k-Space Associates, Inc., a provider of advanced metrology and inspection solutions, announced new machine learning capabilities for its kSA Glass Breakage & Defect Detection tool. The enhancement ...

Researchers from South Korean organisations Pohang University of Science and Technology (POSTECH), Korea Institute of Materials Science (KIMS), and the Hyundai Motor Group, and the Japanese University ...

In an internal memo last year, Meta said the political tumult in the United States would distract critics from the feature’s release. By Kashmir Hill Kalley Huang and Mike Isaac Kashmir Hill reported ...

Researchers report a machine learning approach to predict LPBF defects from up-skin and down-skin angles, suggesting there might be angle-aware process control for metal AM. Laser Powder Bed Fusion ...

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 ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine learning algorithm designed to identify physical anomalies in solar ...

Abstract: This work proposes the use of machine learning-based techniques for enhanced testability and performance calibration of an industrial 79-GHz power amplifier (PA) designed for an automotive ...