Paper Key : IRJ************347
Author: Anjali Sandip Kumbhar,Karande Sakshi Hanumant ,Khatal Sakshi Vishnu,Apeksha Changdev Chavan
Date Published: 06 Nov 2024
Abstract
Agriculture is a key part of the economy, influencing both growth and living standards. However, pests and diseases are major challenges that harm crops and reduce their quality. Traditional methods of identifying pests are time consuming and need experts. Recently, machine learning has been used to make pest and disease detection faster and more accurate. This paper focuses on detecting and classifying insects in crops like sugarcane, pomegranate, guava using machine learning techniques like SVM, KNN, NB, and CNN. The insect detection system uses image processing to find and classify insects quickly, helping farmers identify problems early and improve crop quality and yield.
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