Laser & Optoelectronics Progress, Volume. 56, Issue 15, 151202(2019)

Bullet Appearance Defect Detection Based on Improved Faster Region-Convolutional Neural Network

Xiaoyun Ma1,2,3,4,5、*, Dan Zhu1,2,3,4,5, Chen Jin1,2,4,5, and Xinxin Tong1,2,4,5
Author Affiliations
  • 1 Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 2 Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 3 University of Chinese Academy of Sciences, Beijing 100049, China
  • 4 Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang, Liaoning 110016, China
  • 5 The Key Lab of Image Understanding and Computer Vision, Shenyang, Liaoning 110016, China
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    References(18)

    [2] Shi J W, Guo C Y, Liu H N[J]. Study on detection system of bullet surface defect based on machine visionModular Machine Tool & Automatic Manufacturing Technique, 2013, 59-64.

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    Xiaoyun Ma, Dan Zhu, Chen Jin, Xinxin Tong. Bullet Appearance Defect Detection Based on Improved Faster Region-Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2019, 56(15): 151202

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Dec. 21, 2018

    Accepted: Mar. 5, 2019

    Published Online: Aug. 5, 2019

    The Author Email: Xiaoyun Ma (maxiaoyun@sia.cn)

    DOI:10.3788/LOP56.151202

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