Deep learning-enabled mobile application for efficient and robust herb image recognition.

Journal: Scientific reports
PMID:

Abstract

With the increasing popularity of herbal medicine, high standards of the high quality control of herbs becomes a necessity, with the herb recognition as one of the great challenges. Due to the complicated processing procedure of the herbs, methods of manual recognition that require chemical materials and expert knowledge, such as fingerprint and experience, have been used. Automatic methods can partially alleviate the problem by deep learning based herb image recognition, but most studies require powerful and expensive computation hardware, which is not friendly to resource-limited settings. In this paper, we introduce a deep learning-enabled mobile application which can run entirely on common low-cost smartphones for efficient and robust herb image recognition with a quite competitive recognition accuracy in resource-limited situations. We hope this application can make contributions to the increasing accessibility of herbal medicine worldwide.

Authors

  • Xin Sun
    Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA.
  • Huinan Qian
    Beijing University of Chinese Medicine, Academy of Basic Medicine Sciences, Beijing, China.
  • Yiliang Xiong
    School of Traditional Chinese Classics, Beijing University of Chinese Medicine, Beijing, 100029, China.
  • Yingli Zhu
    School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.
  • Zhaohan Huang
    School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.
  • Feng Yang