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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bing Luo Yun Zhang Guangzhu Yu Xianshan Zhou |
| Copyright Year | 2007 |
| Description | Author affiliation: Guangdong Univ. of Technol., Guangzhou (Bing Luo; Yun Zhang) |
| Abstract | In automatic machine vision inspection for PCB SMT assembly, solder joints inspection is a meaningful but difficult work suffered from variety of complicated images and imbalance of samples. This paper proposed to use ANN ensembles for inspecting classifier, and every simple ANN for ensembles was input with a different feature selected from the image and was trained by genetic algorithm whose fitness function was weighted correctness combined with the minimal margin. ANN linear combination coefficients and training samples' weights were adjusted by AdaBoost algorithm, which corrected a former trained ANN's errors by training other ANNs. Experimental results showed that this approach had got high accuracy, well generalization performance and low calculation cost. |
| Starting Page | 3111 |
| Ending Page | 3115 |
| File Size | 3642905 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424408177 |
| DOI | 10.1109/ICCA.2007.4376934 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-05-30 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Machine vision Inspection Soldering Assembly Surface-mount technology Educational institutions Costs Automation Genetic algorithms Humans genetic algorithm ANN ensemble AdaBoost machine vision pattern recognition |
| Content Type | Text |
| Resource Type | Article |
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