[Evaluation of the performance of the artificial intelligence - enabled snail identification system for recognition of and ].

Abstract

Authors

• J Zhou
  Department of Epidemiology and Health Statistics,Guangdong Pharmaceutical University,Guangzhou,China.
• S Bai
  School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
• L Shi
  Key Laboratory of National Health Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Public Health Research Center of Jiangnan University, Wuxi 214064, China.
• J Zhang
  Department of Mechanical Engineering, Columbia University, 500 West 120th Street, New York, NY 10027, USA.
• C Du
  Yunnan Institute of Endemic Disease Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control Technology, Dali, Yunnan 671000, China.
• J Song
  College of Information Science and Technology, Nanjing Forestry University, Nanjing, China.
• Z Zhang
  Department of Orthopedics, Taizhou People's Hospital, Nanjing Medical University, Taizhou, People's Republic of China; Taizhou Clinical Medical School of Nanjing Medical University, Taizhou, People's Republic of China.
• J Yan
  Department of Cardiology, First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
• A Wu
  Robusoft (Beijing) Co. Ltd, China.
• Y Dong
  China Agricultural University. ylbcdong@cau.edu.cn.
• K Yang
  Key Laboratory of National Health Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Public Health Research Center of Jiangnan University, Wuxi 214064, China.

Keywords

External Resources