CNN-Based Classification of Optically Critical Cutting Tools with Complex Geometry: New Insights for CNN-Based Classification Tasks

• Published in: Sensors (Basel, Switzerland) Vol. 25; no. 5; p. 1575
• Main Authors: Bilal, Mühenad, Podishetti, Ranadheer, Girish, Tangirala Sri, Grossmann, Daniel, Bregulla, Markus
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 04.03.2025; MDPI
• Subjects: Accuracy; Artificial intelligence; Automation; Classification; Computer vision; Cutting tools; Datasets; Deep learning; Geometry; Image processing; Light emitting diodes; Lighting; machining tools: Grad-CAM CNN; Mechanization; Methods; neural network performance; Neural networks; ResNet50; sustainability; tool classification; training performance; Germany; machining tools: Grad-CAM CNN; tool classification; ResNet50; training performance; neural network performance; ResNet152; sustainability

Sustainability has increasingly emphasized the importance of recycling and repairing materials. Cutting tools, such as milling cutters and drills, play a crucial role due to the high demands placed on products used in CNC machining. As a result, the repair and regrinding of these tools have become m...