A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.

Researchers built a photonic synapse that strengthens or erases memory by light color, using a defect to mimic the brain's balanced learning.

Abstract: Semiconductor manufacturers aim to fabricate defect-free wafers in order to improve product quality, increase yields, and reduce costs. Typically, wafer defects form spatial patterns that ...

Recognised by the World Economic Forum, these sites use AI and smart technologies to scale production and strengthen supply chains across industries, shaping the future of manufacturing in South-east ...

At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery ...

New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as well as for bug fixing and identification. Now, one of its new studies ...

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

Shanghai Xiashu Intelligent Science Company Co., Ltd., Shanghai, China. Silk recognition, being one of the most important parts of AOI inspection, plays a crucial role in tracking produced PCB board.

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...