Knowledge Commons of Institute of Automation,CAS
Acupoint Detection Based on Deep Convolutional Neural Network | |
Lingyao,Sun1,2![]() ![]() ![]() | |
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 |
DOI | 10.23919/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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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
1510_final.pdf(1958KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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