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dc.contributor.authorShou, YWen_US
dc.contributor.authorLin, CTen_US
dc.date.accessioned2014-12-08T15:37:20Z-
dc.date.available2014-12-08T15:37:20Z-
dc.date.issued2004-11-01en_US
dc.identifier.issn1057-7122en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TCSI.2004.836861en_US
dc.identifier.urihttp://hdl.handle.net/11536/25674-
dc.description.abstractThis paper proposes a new image-descreening technique based on texture classification using a cellular neural network (CNN) with template trained by genetic algorithm (GA), called GA-CNN. Instead of using the fixed filters for image descreening, we are equipped with a more pliable mechanism for classifications in screening patterns. Using CNN makes it possible to get an accurate texture classification result in a faster speed by its superiority of implementable hardware and the flexible choices of templates. The use of the GA here helps us to look for the most appropriate template for CNNs more adaptively and methodically. The evolved parameters in the template for CNNs can not only provide a quicker classification mechanism but also help us with a better texture classification for screening patterns. After the class of screening patterns in the querying images is determined by the trained GA-CNN-based texture classification. system, the recommendatory filters are induced to solve the screening problems. The induction of the classification in screening patterns has simplified the choice of filters and made it valueless to determine a new structured filter. Eventually, our comprehensive methodology is going to be topped off with more desirable results and the indication for the decrease in time complexity. Index Terms-Cellular neural network (CNN), genetic algorithm (GA), image descreening, texture classification.en_US
dc.language.isoen_USen_US
dc.subjectcellular neural network (CNN)en_US
dc.subjectgenetic algorithm (GA)en_US
dc.subjectimage descreeningen_US
dc.subjecttexture classificationen_US
dc.titleImage descreening by GA-CNN-based texture classificationen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TCSI.2004.836861en_US
dc.identifier.journalIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERSen_US
dc.citation.volume51en_US
dc.citation.issue11en_US
dc.citation.spage2287en_US
dc.citation.epage2299en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000225080800019-
dc.citation.woscount7-
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