Revolutionizing Rice Disease Diagnosis: An Advanced CNN and Vision Transformer Methodology

Abstract

In developing countries particularly, agriculture’s essential role in the economy is indispensable, providing a large population segment with a considerable income source. Among the major crops cultivated across vast regions of the developing countries, rice stands out as a crucial staple food. However, rice crops are largelysusceptible to multiple diseases, causing substantial economic losses in the agricultural sector. To mitigate these challenges, plant pathologists have been actively seeking precise and dependable methods for diagnosing rice plant diseases. Lately, machine learning has become popular incrop remote sensing applications, particularly for the classification of crop diseases. Moreover, deep learning has become a major research area in identifying crop diseases due to its ability to analyze large datasets and deliver accurate results.