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YOLOv8-Based Visual Detection of Road Hazards: Potholes, Sewer Covers, and Manholes
The research assesses the robustness and generalization capabilities of the models through mAP scores calculated across the diverse test scenarios, underlining the significance of YOLOv8 in road hazard detection and infrastructure maintenance.
Making informed decisions in cutting tool maintenance in milling: A KNN based model agnostic approach
Using different machine learning techniques in Tool Condition Monitoring TCM enables a better analysis of the large amount of data of different signals acquired during the machining processes.
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