Detection and State Classification of Bolts Based on Faster R-CNN-Reference-Cited by-同舟云学术

Detection and State Classification of Bolts Based on Faster R-CNN

Published:2022-11-16 Issue: Volume: Page:
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Container-title:2022 28th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
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Author:

Su Zijun¹,Wu Min²,Zhang Zhisheng¹,Wen Haiying³,Xia Zhijie⁴,Zheng Hongzhang¹

Affiliation:

1. School of Mechanical Engineering, Southeast University,Nanjing,China

2. Electrical Co. LTD,Anhui Tianhang Aircraft,Wuhu,China

3. School of Mechanical Engineering, Southeast University,Engineering Research Center of New Light Sources Technology and Equipment, Ministry of Education,Nanjing,China

4. JiangSu Nan Gao Intelligent, Equipment Innovation Center,Nanjing,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province, China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10041021/10041042/10041100.pdf?arnumber=10041100

Reference11 articles.

1. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation;girshick;IEEE Computer Society,2013

2. Defect Detection of Axle Box Cover Device Fixing Bolts in Metro Based on Convolutional Neural Network;y;2020 39th Chinese Control Conference (CCC),2020

3. Fast R-CNN

4. Research on Intelligent Identification of Rock Types Based on Faster R-CNN Method

5. You Only Look Once: Unified, Real-Time Object Detection

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