Tire Speckle Interference Bubble Defect Detection Based on Improved Faster RCNN-FPN

With the development of neural networks, object detection based on deep learning is developing rapidly, and its applications are gradually increasing. In the tire industry, detecting speckle interference bubble defects of tire crown has difficulties such as low image contrast, small object scale, an...

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Detalles Bibliográficos
Autores principales: Yang, Shihao, Jiao, Dongmei, Wang, Tongkun, He, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9143011/
https://www.ncbi.nlm.nih.gov/pubmed/35632316
http://dx.doi.org/10.3390/s22103907

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9143011/
https://www.ncbi.nlm.nih.gov/pubmed/35632316
http://dx.doi.org/10.3390/s22103907

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