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Acupoint Detection Based on Deep Convolutional Neural Network
Lingyao,Sun1,2; Shiying,Sun1; Yuanbo,Fu3; Xiaoguang,Zhao1
2020-09-09
会议名称2020 39th Chinese Control Conference (CCC)
会议日期27-29 July 2020
会议地点Shenyang, China
会议举办国China
摘要

As an important component of Traditional Chinese Medicine (TCM), science of acupoint therapy has achieved significant results in clinical practice, but recognizing and positioning acupoints is heavily depends on the skills of practitioners. In recent years, researchers have proposed a few methods of automatic acupoints detection and positioning, but most of the methods are still based on manual designed features. In this paper, we propose an acupoints detection method based on deep convolutional neural network, and an evaluation method is proposed for acupoint detection. What’s more, we build an acupoint detection dataset. Experiments are performed and a promising result is achieved.

关键词convolutional neural network deep learning acupoint detection convolutional pose machine
DOI10.23919/CCC50068.2020.9188367
收录类别EI
语种英语
七大方向——子方向分类多模态智能
引用统计
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/45007
专题复杂系统认知与决策实验室_先进机器人
作者单位1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
2.University of Chinese Academy of Sciences school of Artificial Intelligence, Beijing 100049, China
3.The Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing Key Laboratory of Acupuncture Neuromodulation, Beijing 100010, China
第一作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Lingyao,Sun,Shiying,Sun,Yuanbo,Fu,et al. Acupoint Detection Based on Deep Convolutional Neural Network[C],2020.
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