Human-computer interaction based health diagnostics using ResNet34 for tongue image classification.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Tongue diagnosis is one of the characteristics of traditional Chinese medicine (TCM), but traditional tongue diagnosis is affected by many factors, and its differential diagnosis results are not widely recognized. The appearance of tongue diagnosis instruments is the product of the modernization of tongue diagnosis, and it has standard and objective advantages in clinical practice. In this study, based on standard tongue images, a tongue image dataset and detection model were constructed. And based on the deep learning convolutional neural network (CNN) algorithm and visual question answering technology, a human-computer interaction intelligent health detector for tongue image recognition is constructed.

Authors

  • Qingbin Zhuang
    Fine Art and Design College, Quanzhou Normal University, Quanzhou 362000, China.
  • Senzhong Gan
    Institute of Creativity and Innovation Xiamen University, Zhangzhou Campus, Fujian, 363105, China. Electronic address: gansenzhong@xmu.edu.cn.
  • Liangyu Zhang
    Fine Art and Design College, Quanzhou Normal University, Quanzhou, 362000, China.