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Deep Multimodel Cascade Method Based on CNN and Random Forest for Pharmaceutical Particle Detection

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成果类型:
期刊论文
作者:
Zhang, Hui*;Zhao, Miao;Liu, Li*;Zhong, Hang;Liang, Zhicong;...
通讯作者:
Zhang, Hui;Liu, Li
作者机构:
[Zhang, Hui] Hunan Univ, Sch Robot, Changsha 410082, Hunan, Peoples R China.
[Zhang, Hui; Liang, Zhicong; Zhao, Miao] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410012, Peoples R China.
[Liu, Li; Zhong, Hang; Wang, Yaonan; Zhou, Xianen] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.
[Yang, Yimin] Lakehead Univ, Dept Comp Sci, Thunder Bay, ON P7B 5E1, Canada.
[Wu, Q. M. Jonathan] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada.
通讯机构:
[Zhang, Hui; Liu, Li] H
Hunan Univ, Sch Robot, Changsha 410082, Hunan, Peoples R China.
Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Hunan, Peoples R China.
语种:
英文
关键词:
Faster R-CNN;k-means;moving foreign particles visual detection;pharmaceutical detection;random forest (RF);trajectory space feature vector
期刊:
IEEE Transactions on Instrumentation and Measurement
ISSN:
0018-9456
年:
2020
卷:
69
期:
9
页码:
7028-7042
基金类别:
Manuscript received June 14, 2019; revised November 18, 2019; accepted January 28, 2020. Date of publication February 13, 2020; date of current version August 11, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61971071 and Grant 61701047, in part by the National Key Research and Development Program of China under Grant 2018YFB1308200, in part by the Hunan Key Laboratory of Intelligent Robot Technology in Electronic Manufacturing under Grant IRT2018009, in part by the Hunan Key Project of Research and Development Plan under Grant 2018GK2022, and in part by the Changsha Science and Technology Project under Grant kq1907087. The Associate Editor coordinating the review process was Shutao Li. (Corresponding authors: Hui Zhang; Li Liu.) Hui Zhang is with the School of Robotics, Hunan University, Changsha 410082, China, and also with the College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410012, China (e-mail: zhanghuihby@126.com).
机构署名:
本校为其他机构
院系归属:
电气与信息工程学院
摘要:
The quality detection of pharmaceutical liquid products is inevitable and crucial in drug manufacture because drugs contaminated with foreign particles are definitely not to be used. However, with the current detection methods, it is still a challenge to detect and identify the small moving particles using an imaging system. In this article, a deep multimodel cascade method combining single-frame image and multiframe images processing method to detect and identify foreign particles is proposed. The proposed method consists of three stages. Firs...

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