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

Xiaoyun Ma; Dan Zhu; Chen Jin; Xinxin Tong

doi:10.3788/LOP56.151202

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 15 >Page 151202 > Article

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

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

Xiaoyun Ma^{1、2、3、4、5、*}, Dan Zhu^{1、2、3、4、5}, Chen Jin^{1、2、4、5}, and Xinxin Tong^{1、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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DOI: 10.3788/LOP56.151202 Cite this Article Set citation alerts

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 Copy Citation Text

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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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