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dc.contributor.author 정재진 -
dc.contributor.author 심승보 -
dc.contributor.author 원형필 -
dc.contributor.author 구교권 -
dc.date.accessioned 2021-09-27T12:30:05Z -
dc.date.available 2021-09-27T12:30:05Z -
dc.date.created 2021-05-07 -
dc.date.issued 2021-04 -
dc.identifier.issn 1975-5066 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/15336 -
dc.description.abstract This paper proposes a deep learning algorithm for estimating pig weight. The proposed algorithm estimates the weight of a pig using the point cloud obtained through a mobile device. The proposed model is based on the PointNet which is widely used in the point cloud data. Through the optimization of the PointNet, the proposed method not only improves the accuracy, but also reduces the computational complexity. The accuracy (82.4 %) of the proposed method was about 3 % higher than that of the conventional method (79.4 %). Also, the numbers of the trainable parameters for the PointNet and the proposed method were 3,114,771 and 150,554, respectively. That is, the proposed method used only 5 % of trainable parameters compared to the PointNet. The developed model makes it easier and faster to measure the weight of a pig than the conventional method. -
dc.language Korean -
dc.publisher 대한임베디드공학회 -
dc.title 이동형 디바이스를 이용한 딥러닝 기반의 돼지 무게 추정 알고리즘 -
dc.title.alternative Deep Learning-Based Pig Weight Estimation Algorithm Using Mobile Devices -
dc.type Article -
dc.identifier.doi 10.14372/IEMEK.2021.16.2.59 -
dc.identifier.bibliographicCitation 대한임베디드공학회논문지, v.16, no.2, pp.59 - 64 -
dc.identifier.kciid ART002710891 -
dc.description.isOpenAccess FALSE -
dc.subject.keywordAuthor 3D classification -
dc.subject.keywordAuthor PointNet -
dc.subject.keywordAuthor 3D point cloud -
dc.citation.endPage 64 -
dc.citation.number 2 -
dc.citation.startPage 59 -
dc.citation.title 대한임베디드공학회논문지 -
dc.citation.volume 16 -
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Division of Intelligent Robot 1. Journal Articles

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