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Crop Disease Prediction using Deep Learning Techniques - A Review

Gargi Sharma, Gourav Shrivastava

2022International Journal of Computer Science and Engineering12 citationsDOIOpen Access PDF

Abstract

In agriculture, AI is bringing about a revolution by replacing traditional methods with more efficient ones and contributing to a better world. Artificial Intelligence and machine learning enable 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, 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 summarize recent crop disease detection research papers. Multiple deep learning algorithms demonstrate the current solutions for different crop disease diagnoses in this research. I hope this report will be useful to other crop disease detection researchers.

Topics & Concepts

Deep learningAgricultural engineeringAgricultureArtificial intelligenceCropQuality (philosophy)Computer scienceBiotechnologyMachine learningEngineeringAgronomyGeographyBiologyPhilosophyArchaeologyEpistemologySmart Agriculture and AISpectroscopy and Chemometric Analyses
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