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29Mar 26
explainable-hybrid-ai-cad-framework-for-advanced-prediction-of-steel-surface-defects-–-scientific-reports

Explainable hybrid AI CAD framework for advanced prediction of steel surface defects – Scientific Reports

References Zhong, H. et al. LiFSO-Net: A lightweight feature screening optimization network for complex-scale flat metal defect detection. Knowl. Based Syst. 304, 112520. https://doi.org/10.1016/j.knosys.2024.112520 (2024). Google Scholar  Tang, B., Chen, L., Sun, W. & Lin, Z. Review of surface defect detection of steel products based on machine vision. IET Image Proc. 17(2), 303–322. https://doi.org/10.1049/ipr2.12647 (2023).

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28Mar 26
aamu-named-regional-lead-for-amazon-web-services-–-machine-learning-university

AAMU named regional lead for Amazon Web Services – Machine Learning University

Alabama A&M University (AAMU) has been selected as a regional lead institution for Amazon Web Services–Machine Learning University (AWS-MLU), further elevating the university's role as a leader in artificial intelligence and machine learning education, research and workforce development. AAMU joins Delaware State University, Howard University, City Colleges of Chicago and Oklahoma City Community College as

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28Mar 26
how-ai-and-machine-vision-are-revolutionising-cheese-making-–-drives&controls

How AI and machine vision are revolutionising cheese-making – Drives&Controls

27 March 2026   The cheese wheels are removed automatically from warehouse shelves. A German cheese-maker is using a vision system and machine-learning algorithms to detect any defects in its cheeses, thus boosting its efficiency, reducing its need for manual inspections, cutting waste, and improving quality control. Cheese consumption is booming globally, and producers are facing

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