DETECTION OF DISEASES IN TOMATO PLANTS USING DEEP LEARNING

Authors

  • Rushi Chaudhari SCOE Pune, Savitribai Phule Pune University, Maharashtra,India
  • Rohan Marathe SCOE Pune, Savitribai Phule Pune University, Maharashtra,India
  • Rohan Rane SCOE Pune, Savitribai Phule Pune University, Maharashtra,India

Keywords:

Tomatoes,, Disease Detection,, CNN,, VGG19.

Abstract

Crop disease is increasingly becoming a concern for the farmers due to many factors such as climate change, growing resistance of pathogens, etc. An ill-diagnosed disease, leading to incorrect treatment ultimately affects the qualityand quantity of yield, thereby causing financial distress to the farmer. The proposed system aims to serve as a tool for the farmers to identify diseases in tomato plants, using a smartphone application as a means of interface and a Convolutional Neural Network (CNN) for identification of diseases. Processing and storage constraints are eliminated with the use of Cloud platform. We also aim to make the application more comprehensive by suggesting the remedies and preventive measures for the detected disease. The proposed system is highly scalable and aims at achieving a higher accuracy in disease detection by surveying the drawbacks of the existing system.

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Published

2021-03-27

Issue

2019: ICSD

Section

Articles

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