preprintJan 5, 2020GREEN OA

PlantDoc

Indian Institute of Technology Gandhinagar

Indexed inarxivcrossref

Abstract

India loses 35% of the annual crop yield due to plant diseases. Early detection of plant diseases remains difficult due to the lack of lab infrastructure and expertise. In this paper, we explore the possibility of computer vision approaches for scalable and early plant disease detection. The lack of availability of sufficiently large-scale non-lab data set remains a major challenge for enabling vision based plant disease detection. Against this background, we present PlantDoc: a dataset for visual plant disease detection. Our dataset contains 2,598 data points in total across 13 plant species and up to 17 classes of diseases, involving approximately 300 human hours of effort in annotating internet scraped…

Citation impact

582
total citations
FWCI
46.01
Percentile
100%
References
22
Citations per year

Authors

6

Topics & keywords

Keywords
  • Plant disease
  • Computer science
  • Scalability
  • Task (project management)
  • Artificial intelligence
  • Set (abstract data type)
  • Scale (ratio)
  • The Internet
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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