Surface Defect Detection of Remanufactured Products by Using the Improved Yolov5
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-52649-7_19
Reference20 articles.
1. Chen L, Yao X, Xu P et al (2021) Rapid surface defect identification for additive manufacturing with in-situ point cloud processing and machine learning. Virtual Phys Prototyping 16(1):50–67
2. Chen W, Huang H, Peng S et al (2021) YOLO-face: a real-time face detector. Vis Comput 37(4):805–813
3. Gai R, Chen N,Yuan H (2021) A detection algorithm for cherry fruits based on the improved YOLO-v4 model. Neural Comput Appl
4. Golinska-Dawson P, Kawa A (2011) Remanufacturing in automotive industry: Challenges and limitations. J Ind Eng Manag (JIEM) 4(3):453–466
5. He Y, Ma W, Li Y et al (2023) An Octree-Based Two-Step method of surface defects detection for remanufacture. Int J Precis Eng Manuf-Green Technol 10(2):311–326
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