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An Optimization Method for Personnel Statistics Based on YOLOv4 + DPAC

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成果类型:
期刊论文
作者:
Chen, Wenhui;Wu, Guanchen;Jung, Hoekyung
通讯作者:
Hoekyung Jung
作者机构:
[Chen, Wenhui] Hengyang Normal Univ, Coll Comp Sci & Technol, Hengyang 421002, Peoples R China.
[Wu, Guanchen] Guizhou Commun Polytech, Dept Informat Engn, Guiyang 551400, Peoples R China.
[Jung, Hoekyung] Paichai Univ, Dept Comp Sci & Engn, 155-40 Baejae Ro, Daejeon 35345, South Korea.
通讯机构:
[Hoekyung Jung] D
Department of Computer Science and Engineering, Paichai University, 155-40 Baejae-ro, Daejeon 35345, Korea<&wdkj&>Author to whom correspondence should be addressed.
语种:
英文
关键词:
deep learning;you only look once (YOLO);number of people detection;distributed probability-adjusted confidence (DPAC)
期刊:
Applied Sciences-Basel
ISSN:
2076-3417
年:
2022
卷:
12
期:
17
页码:
8627-
基金类别:
This research was supported by the MIST (Ministry of Science and ICT), Korea, under the Innovative Human Resource Development for Local Intellectualization support program (IITP-2022-RS-2022-00156334), supervised by the IITP (Institute for Information and Communications Technology Planning and Evaluation).
机构署名:
本校为第一机构
院系归属:
计算机科学与技术学院
摘要:
Compared to traditional detection methods, image-based flow statistics that determine the number of people in a space are contactless, non-perceptual, and high-speed statistical methods that have broad application prospects and potential economic value in business, education, transportation, and other fields. In this paper, we propose that the distributed probability-adjusted confidence (DPAC) function can optimize the reliability of model prediction according to the actual situation. That is, the reliability can be adjusted using the distribution characteristics of the target in the field of ...

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