CROP DISEASE PREDICTION USING DEEP LEARNING TECHNIQUES - A REVIEW

ICTACT Journal on Data Science and Machine Learning ( Volume: 3 , Issue: 3 )

Abstract

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In agriculture, AI is bringing about a revolution by replacing traditional methods with more efficient ones and thereby contributing to a better world. Artificial Intelligence and machine learning are enabling the development and implementation of devices that can identify and control plants, weeds, pests and diseases through remote sensing. Plant disease lowers the quantity and quality of food, fiber, and biofuel crops, all of which are important to the Indian economy. In addition to reducing waste, using Deep learning technologies can increase quality and speed up market access for farmers. Here, we summaries recent crop disease detection research papers in a concise manner. In this research, multiple deep learning algorithms are used to demonstrate the current solutions for different crop disease diagnosis. I hope this report will be useful to other crop disease detection researchers.

Authors

Gargi Sharma1, Gourav Shrivastava2
Sage University, India1,2

Keywords

Crop Disease, Deep Learning, CNN

Published By
ICTACT
Published In
ICTACT Journal on Data Science and Machine Learning
( Volume: 3 , Issue: 3 )
Date of Publication
June 2022
Pages
312-315
DOI

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