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New AI model revolutionizes medical imaging with 90% less computing power
Rice University’s MetaSeg matches U-Net accuracy using 90% fewer parameters, making AI medical image segmentation faster, cheaper, and more accessible for hospitals and researchers.
Tech Xplore on MSN
From cells to semiconductors: AI reconstructs microscopic 3D worlds from electron microscopy
The Korea Research Institute of Standards and Science (KRISS) has developed an artificial intelligence (AI)-based image ...
When it comes to generative AI news, Meta has taken somewhat of a backseat as of late. However, on Wednesday, the tech giant unveiled research on image segmentation that could have a large impact on ...
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