Convolutional Neural Network based Surface Mounted Component Classification using Size Information
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 문영식 | - |
dc.date.accessioned | 2021-06-22T10:26:17Z | - |
dc.date.available | 2021-06-22T10:26:17Z | - |
dc.date.created | 2021-02-18 | - |
dc.date.issued | 2019-01 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/3576 | - |
dc.description.abstract | In Automatic Optical Inspection (AOI), Surface Mounted Components (SMC) classification is a basic step for device recycling or defect detection. In classification, Convolutional Neural Network (CNN) is widely used, but there is limitation to classify SMC with similar appearances. We propose a CNN model with size information for SMC classification. We modify general CNN model by concatenating the size information to the FC layer. Our model is applicable to SMC with various sizes and achieves 91.1% performance for classification. Our model is capable 119 FPS on 128 by 128 RGB image. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEIE | - |
dc.title | Convolutional Neural Network based Surface Mounted Component Classification using Size Information | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 문영식 | - |
dc.identifier.bibliographicCitation | International Conference on Green and Human Information Technology , pp.1 - 3 | - |
dc.relation.isPartOf | International Conference on Green and Human Information Technology | - |
dc.citation.title | International Conference on Green and Human Information Technology | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 3 | - |
dc.type.rims | ART | - |
dc.description.journalClass | 3 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
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