Detecting defects in fused deposition modeling based on improved YOLO v4

Detecting defects in fused deposition modeling based on improved YOLO v4

Fused deposition modeling comes with many conveniences for the manufacturing industry, but many defects tend to appear in actual production due to the problems of the FDM mechanism itself. Although some deep learning-based object detection models show excellent performance in detecting defects in th...

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Bibliographic Details
Main Authors: Luyang Xu, Xiaoxun Zhang, Fang Ma, Gaoyuan Chang, Cheng Zhang, Jiaming Li, Shuxian Wang, Yuanyou Huang
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:Materials Research Express
Subjects:
additive manufacturing
fused deposition modeling
deep learning
light weight network
YOLO v4
Online Access:https://doi.org/10.1088/2053-1591/acf6f9

Internet

https://doi.org/10.1088/2053-1591/acf6f9

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