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QQ767172261/Deep-learning-target-detection-uses-YOLOv8-to-train-the-glass-surface-defect-detection-data-set-from

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QQ767172261/Yolov8-training-is-used-in-deep-learning-target-detection-to-use-the-road-defect-data-set-to-identif

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Frontiers

Advanced AI for missing modality learning and uncertainty‑aware medical image analysis

Modern medical imaging increasingly relies on artificial intelligence to support detection, diagnosis, and prognostic ...
Tech Xplore

Reliably detecting and clearly explaining deepfake images

Artificial intelligence can now generate images that are virtually indistinguishable from real ones. Researchers at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation ...
Ophthalmology Times

Offline smartphone AI accurately detects DR, glaucoma, and AMD in real-world study

An offline, point-of-care algorithm on a smartphone fundus camera generated disease-specific outputs without cloud connectivity, addressing a major deployment barrier in low-resource screening ...
Semiconductor Engineering

Observability Is A Missing Layer In AI-Era Chiplet Design

In next-generation silicon, AI can interpret system behavior at scale, but only if observability is designed into the fabric ...
IMV Europe

Roboflow integrates Nvidia synthetic data tools to boost manufacturing defect detection

Roboflow's workflow combines real and synthetic training data to develop defect detection models for manufacturing applications (Image: Roboflow) Roboflow integrates Nvidia simulation tools to train m ...