Deep Learning-Based Classification Methods for Detection of Diseases in Rice Leaves – A Review

Abstract

Cultivating rice is crucial in India to meet demands of a growing population. In order to improve crop yield, it's essential to address factors like diseases caused by bacteria, fungi, and viruses. Detecting and managing these diseases is vital, and one effective approach is employing rice plant disease detection methods. Deep learning techniques, known for their ability to analyse data, are used for disease identification in plants. This work explores various deep learning approaches for detecting rice plant disease. Deep learning, particularly in computer vision, has shown significant progress in detecting plant diseases. The study compares the effectiveness deep learning mechanisms, demonstrating superior performance of deep learning models. Utilizing deep learning can help prevent major crop losses by detecting leaf diseases through image analysis.