Abstrait

Artificial Intelligence (AI) based Chilly Crop Disease Detection System

Nived Mangji, Gaurav Shet, Sameer Rane, Rajaram Parab*, Harish Velingkar, Chaitali Karekar, Laxmikant Bordekar, Vrushali Prabhudesa

The major cause for decrease in the quality and production of agricultural productivity is because of plant diseases. The detection and control of plant diseases pose significant challenges for farmers. Therefore, timely and accurate diagnosis of these diseases is crucial to enable farmers to take appropriate measures and prevent further losses. Early detection allows for prompt action, and thus, it is essential for farmers to be able to identify and diagnose plant diseases at the earliest possible stage. The work focuses on the approach based on deep learning for detection of diseases of chilly plants for two main leaf diseases i.e. curl leaf disease and bacterial leaf spot. This work proposes an Android application which will help farmers to detect chilly diseases by uploading leaf images to the system. The system has a set of algorithms which can identify the type of diseases and provide the necessary remedies for that particular disease. Input image given by the user undergoes several processing steps to detect the disease and results are returned back to the user via android application

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Chemical Abstracts Service (CAS)
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Open J Gate
Academic Keys
ResearchBible
CiteFactor
Cosmos IF
Electronic Journals Library
RefSeek
Hamdard University
European Federation for Information Technology in Agriculture (EFITA)
IndianScience.in
Scholarsteer
International Innovative Journal Impact Factor (IIJIF)
International Institute of Organised Research (I2OR)
Cosmos
Secret Search Engine Labs
Euro Pub

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