Surface Defects Detection of Cylindrical High-Precision Industrial Parts Based on Deep Learning Algorithms: A Review

High-precision cylindrical parts are critical components across various industries including aerospace, automotive, and manufacturing. Since these parts play a pivotal role in the performance and safety of the systems they are integrated into, they are often subject to stringent quality control meas...

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Veröffentlicht in:	Operations Research Forum Jg. 5; H. 3; S. 58
Hauptverfasser:	Wei, Li, Solihin, Mahmud Iwan, Saruchi, Sarah ‘Atifah, Astuti, Winda, Hong, Lim Wei, Kit, Ang Chun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.09.2024 Springer Nature B.V
Schlagworte:	Aerospace industry Algorithms Applications of Mathematics Automation Business and Management Cameras Catastrophic wear Computer vision Corrosion Critical components Data acquisition Deep learning Defects Design Image acquisition Innovation and Infrastructure Machine learning Manufacturing Math Applications in Computer Science Mathematical and Computational Engineering Neural networks Operations Research/Decision Theory Optimization Performance degradation Quality control Review State-of-the-art reviews Surface defects Topical Collection on Math for SDG 9 - Industry Uniqueness Deep learning Computer vision High-precision cylindrical parts Image processing Optical illumination Anomaly detection Defect detection
ISSN:	2662-2556, 2662-2556
Online-Zugang:	Volltext
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