计算机科学
人工智能
工作量
一致性(知识库)
钥匙(锁)
针灸科
过程(计算)
深度学习
公制(单位)
机器学习
模式识别(心理学)
医学
工程类
操作系统
病理
替代医学
计算机安全
运营管理
作者
Shiying Sun,Hongduo Xu,Lingyao Sun,Yuanbo Fu,Yujia Zhang,Xiaoguang Zhao
标识
DOI:10.1109/ijcnn55064.2022.9892098
摘要
As an important component of Traditional Chinese Medicine (TCM), the acupoint therapy has achieved significant success in clinical practice. However, at present, the effect of acupoint therapy heavily depends on the skills of doctors and the acupuncture medical resources are seriously insufficient. The introduction of artificial intelligence technology in acupoint therapy can reduce the workload of doctors and ensure the consistency of acupoint operations, which is of great significance. The key process of acupoint therapy is acupoint detection. In this paper, we apply the deep learning method in automatic acupoint detection using images and propose an improved High-Resolution Network (HRNet) method for hand acupoint detection. What's more, we build a hand acupoint detection dataset and propose an evaluation metric. Experiments on the proposed dataset verify the effectiveness of the proposed method.
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