CNN‐based reference comparison method for classifying bare PCB defects

Author:

Wei Peng1,Liu Chang2,Liu Mengyuan3,Gao Yunlong1,Liu Hong2

Affiliation:

1. Department of AutomationXiamen UniversityXiamenPeople's Republic of China

2. Key Laboratory of Machine PerceptionShenzhen Graduate SchoolPeking UniversityShenzhenPeople's Republic of China

3. Nanyang Technological UniversitySingaporeSingapore

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Reference22 articles.

1. ParkT.‐H. KimH.‐J.: ‘Path planning of automatic optical inspection machines for PCB assembly systems’.2005 Int. Symp. Computational Intelligence in Robotics and Automation Espoo Finland June 2005 pp.249–254

2. A survey on industrial vision systems, applications and tools;Malamas E.N.;Image Vis. Comput.,2003

3. Automatic PCB inspection algorithms: a survey;Moganti M.;Comput. Vis. Image Underst.,1996

4. Automated inspection of printed circuit boards through machine vision;Wu W.‐Y.;Comput. Ind.,1996

5. IbrahimZ. Al‐AttasS.A.R. AsparZ.et al.: ‘Performance evaluation of wavelet‐based PCB defect detection and localization algorithm’.2002 IEEE Int. Conf. Industrial Technology (IEEE ICIT '02) Bangkok Thailand December 2002 vol. 1 pp.226–231

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