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컨벌루션 신경망을 사용한 다중 차선 인식

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dc.contributor.author박희문-
dc.contributor.author황광복-
dc.contributor.author배준경-
dc.contributor.author박진현-
dc.date.accessioned2022-12-26T09:20:36Z-
dc.date.available2022-12-26T09:20:36Z-
dc.date.issued2022-
dc.identifier.issn1229-604X-
dc.identifier.issn2508-3805-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/2319-
dc.description.abstractIn this study, the multi-lane detection problem is expressed as a CNN-based regression problem, and the lane boundary coordinates are selected as outputs. In addition, we described lanes as fifth-order polynomials and distinguished the ego lane and the side lanes so that we could make the prediction lanes accurately. By eliminating the network branch arrangement and the lane boundary coordinate vector outside the image proposed by Chougule’s method, it was possible to eradicate meaningless data learning in CNN and increase the fast training and performance speed. And we confirmed that the average prediction error was small in the performance evaluation even though the proposed method compared with Chougule’s method under harsher conditions. In addition, even in a specific image with many errors, the predicted lanes did not deviate significantly, meaningful results were derived, and we confirmed robust performance.-
dc.format.extent8-
dc.language한국어-
dc.language.isoKOR-
dc.publisher한국기계기술학회-
dc.title컨벌루션 신경망을 사용한 다중 차선 인식-
dc.title.alternativeMulti-lanes Detection using Convolutional Neural Network-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.17958/ksmt.24.2.202204.288-
dc.identifier.bibliographicCitation한국기계기술학회지, v.24, no.2, pp 288 - 295-
dc.citation.title한국기계기술학회지-
dc.citation.volume24-
dc.citation.number2-
dc.citation.startPage288-
dc.citation.endPage295-
dc.identifier.kciidART002838607-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorMulti-lanes detection(다중 차선 인식)-
dc.subject.keywordAuthorConvolutional neural network(컨벌루션 신경망)-
dc.subject.keywordAuthorfifth-order polynomial(5차 다항식)-
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융합기술공과대학 > Division of Mechatronics Engineering > Journal Articles

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