Plant Leaves Disease detection by using Machine Learning & Image Recognition Techniques

Plant Leaves Disease detection by using Machine Learning & Image Recognition Techniques.

1Sudhiksha.V, 2Sufiyaan Ali Khan, 3 Suhaas.M 4Sumanth.G, 5Sumedh Acharya.CH, 6 Sumedh.V, 7 Prof.Shiva Kumar
123456Student, 7 Assistant Professor

Department of Artificial Intelligence & Machine Learning Malla Reddy University, Hyderabad.

Abstract:
Plant diseases are a big issue in today's world, causing significant production and economic losses as well as a drop in both the quality and quantity of agricultural commodities. As a result, plant disease detection technologies and solutions have garnered increased attention in large-scale crop monitoring. Farmers face significant challenges when transitioning from one disease management regime to another. In this research, we examine the need for a simple plant leaf disease detection system, focusing on tomato leaf diseases, to aid in tomato crop health and harvest developments. Early diagnosis of crop health and illness can aid in disease control through correct management measures. This strategy will increase agricultural productivity. This study also examines the benefits and limits of several prospective technologies that farmers and agricultural specialists may employ to rapidly and effectively identify plant diseases, allowing for prompt intervention and the prevention of additional crop loss. As a result of this application, we can help to assure plant security while also having a good influence on agriculture.

Keywords: Disease detection, image capture, image recognition, machine learning models, pre-processing, categorization.