Anomaly Segmentation Based on Depth Image for Quality Inspection Processes in Tire Manufacturing
This paper introduces and implements an efficient training method for deep learning–based anomaly area detection in the depth image of a tire. A depth image of 16 bit integer size is used in various fields, such as manufacturing, industry, and medicine. In addition, the advent of the 4th Industrial...
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Autores principales: | Dongbeom Ko, Sungjoo Kang, Hyunsuk Kim, Wongok Lee, Yousuk Bae, Jeongmin Park |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/f566b8493874411788ce35d4ea748587 |
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