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A Survey: Plant Disease Detection Using Deep Learning

Author

Listed:
  • Anshul Tripathi

    (Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), India)

  • Uday Chourasia

    (Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), India)

  • Priyanka Dixit

    (Gandhi Prodyogiki Vishwavidyalaya (RGPV), India)

  • Victor Chang

    (Aston University, UK)

Abstract

Agriculture occupation has been the prime occupation in India since the primeval era. Nowadays, the country is ranked second in the prime occupations threatening global warming. Apart from this, diseases in plants are challenging to this prime source of livelihood. The present research can help in recognition of different diseases among plants and help to find out the solution or remedy that can be a defense mechanism in counter to the diseases. Finding diseases among plant DL is considered to the most perfect and exact paradigms. Four labels are classified as “bacterial spot,” “yellow leaf curl virus,” “late blight,” and “healthy leaf.” An exemplar model of the drone is also designed for the purpose. The said model will be utilized for a live report for extended large crop fields. In this exemplar drone model, a high-resolution camera is attached. The captured images of plants will act as software input. On this basis, the software will immediately tell which plants are healthy and which are diseased.

Suggested Citation

  • Anshul Tripathi & Uday Chourasia & Priyanka Dixit & Victor Chang, 2021. "A Survey: Plant Disease Detection Using Deep Learning," International Journal of Distributed Systems and Technologies (IJDST), IGI Global, vol. 12(3), pages 1-26, July.
    • Handle: RePEc:igg:jdst00:v:12:y:2021:i:3:p:1-26
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