어안렌즈 카메라로 획득한 영상에서 차량 인식을 위한 딥러닝 기반 객체 검출기
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tang Quang Hieu | - |
dc.contributor.author | 연승호 | - |
dc.contributor.author | 김재민 | - |
dc.date.available | 2020-07-10T04:12:40Z | - |
dc.date.created | 2020-07-06 | - |
dc.date.issued | 2019 | - |
dc.identifier.issn | 1229-7771 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/2659 | - |
dc.description.abstract | This paper presents a deep learning-based object detection method for recognizing vehicles in images acquired through cameras installed on ceiling of underground parking lot. First, we present an image enhancement method, which improves vehicle detection performance under dark lighting environment. Second, we present a new CNN-based multiscale classifiers for detecting vehicles in images acquired through cameras with fisheye lens. Experiments show that the presented vehicle detector has better performance than the conventional ones. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | 한국멀티미디어학회 | - |
dc.title | 어안렌즈 카메라로 획득한 영상에서 차량 인식을 위한 딥러닝 기반 객체 검출기 | - |
dc.title.alternative | Deep Learning based Object Detector for Vehicle Recognition on Images Acquired with Fisheye Lens Cameras | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 김재민 | - |
dc.identifier.doi | 10.9717/kmms.2019.22.2.128 | - |
dc.identifier.bibliographicCitation | 멀티미디어학회논문지, v.22, no.2, pp.128 - 135 | - |
dc.relation.isPartOf | 멀티미디어학회논문지 | - |
dc.citation.title | 멀티미디어학회논문지 | - |
dc.citation.volume | 22 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 128 | - |
dc.citation.endPage | 135 | - |
dc.type.rims | ART | - |
dc.identifier.kciid | ART002441243 | - |
dc.description.journalClass | 2 | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Deep Learning | - |
dc.subject.keywordAuthor | Vehicle Detection | - |
dc.subject.keywordAuthor | Fisheye Lens Cameras | - |
dc.subject.keywordAuthor | Convolutional Neural Network | - |
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