Plant Disease Identification using Artificial Intelligence: Machine Learning Approach

Jubin Dipakkumar Kothari (2018). Plant Disease Identification using Artificial Intelligence: Machine Learning Approach. International Journal of Innovative Research in Computer and Communication Engineering, 7(11), 11082-11085.

4 Pages Posted: 14 Jan 2021 Last revised: 8 Feb 2021

Date Written: 2018

Abstract

Computerization in the field of agriculture sees an extraordinary achievement in numerous farming perspectives, including detection of different plant diseases. The focal point of pretty much every nation has moved towards the mechanization of agriculture to achieve exactness and precision and to serve the consistently expanding request of food. Among the significant difficulties in agriculture, plant disease detection is a critical factor influencing the result of cultivating. Quality of vegetables, organic products, vegetables and grains is influenced by plant disease, and hefty misfortune underway and therefore monetary loses are watched, so there is a prerequisite of quick and viable plant disease detection and evaluation strategies. This paper investigates the manners by which machine learning models can be applied to improve the cycle of plant disease detection in beginning phases to improve grain security and manageability of the agro-biological system.

Keywords: Machine Learning, Neural Networks, Supervised learning

Suggested Citation

Kothari, Jubin Dipakkumar, Plant Disease Identification using Artificial Intelligence: Machine Learning Approach (2018). Jubin Dipakkumar Kothari (2018). Plant Disease Identification using Artificial Intelligence: Machine Learning Approach. International Journal of Innovative Research in Computer and Communication Engineering, 7(11), 11082-11085., Available at SSRN: https://ssrn.com/abstract=3729753

Jubin Dipakkumar Kothari (Contact Author)

Campbellsville University ( email )

1 University dr
Campblellsville, KY Kentucky 42718
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
1,908
Abstract Views
3,952
Rank
16,788
PlumX Metrics