计算机科学与探索 ›› 2023, Vol. 17 ›› Issue (2): 303-323.DOI: 10.3778/j.issn.1673-9418.2208052
吴欣,徐红,林卓胜,李胜可,刘慧琳,冯跃
出版日期:
2023-02-01
发布日期:
2023-02-01
WU Xin, XU Hong, LIN Zhuosheng, LI Shengke, LIU Huilin, FENG Yue
Online:
2023-02-01
Published:
2023-02-01
摘要: 随着技术的快速发展和计算能力的提高,深度学习在舌象分类领域将得到广泛的应用。舌诊图像的舌象分类是中医舌诊客观化的重要组成部分。传统的舌诊是在基础理论的指导下,借助个人经验所做出的理解和判断,因而会具有一定的差异性和模糊性,影响诊断的可重复性。为了减少主观判断的误差,许多研究人员致力于通过深度学习实现中医舌诊的客观化、定量化和自动化。主要对基于深度学习的舌象分类方法研究现状进行分析梳理和归纳总结。在舌象分类研究中,以各类深度学习方法作为研究对象,将其划分为基于早期神经网络、卷积神经网络、区域卷积神经网络、迁移学习以及其他方法进行总结分析;对舌诊中的中医证候和疾病以及体质分类进行了讨论;用Kaggle上的公开舌诊数据集进行5折交叉验证实验,数据集为小样本齿痕舌,评估了基于深度学习和迁移学习分类方法;对舌诊图像质量、构建数据集方式、特征提取、单标签和多标签分类的研究发展进行了探讨和展望。
吴欣, 徐红, 林卓胜, 李胜可, 刘慧琳, 冯跃. 深度学习在舌象分类中的研究综述[J]. 计算机科学与探索, 2023, 17(2): 303-323.
WU Xin, XU Hong, LIN Zhuosheng, LI Shengke, LIU Huilin, FENG Yue. Review of Deep Learning in Classification of Tongue Image[J]. Journal of Frontiers of Computer Science and Technology, 2023, 17(2): 303-323.
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