Region-aggregated attention CNN for disease detection in fruit images.

Journal: PloS one
Published Date: Oct 25, 2021

Abstract

BACKGROUND: Diseases and pests have a profound effect on a yearly harvest and productivity in agriculture. A precise and accurate detection of the diseases and pests could facilitate timely treatment and management of the diseases and pests and lessen the resultant loss in economy and health. Herein, we propose an improved design of the disease detection system for plant images.

Authors

  • Chang Hee Han
    Department of Computer Science and Engineering, Sejong University, Seoul, South Korea.
  • Eal Kim
    Department of Computer Science and Engineering, Sejong University, Seoul 05006, Korea.
  • Tan Nhu Nhat Doan
    Department of Computer Science and Engineering, Sejong University, Seoul, Korea.
  • Dongil Han
    Department of Computer Science and Engineering, Sejong University, Seoul, Korea.
  • Seong Joon Yoo
    Department of Computer Science and Engineering, Sejong University, Seoul, Korea.
  • Jin Tae Kwak
    Center for Interventional Oncology, National Institutes of Health, Bethesda, MD, 20892, USA.

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