Rice blast is one of the most serious plant diseases. Many rice blast management
approaches require know-how of experienced farmers or agronomists. Monitoring the farm …

Rice production has faced numerous challenges in recent years, and traditional methods
are still being used to detect rice diseases. This research project developed an automated …

Rice blast disease is the major problem in all over the world of agriculture sector. The early
detection of this disease will prevent the huge economic loss for the farmer. This paper …

Based on principal component analysis and back propagation neural network (PCA-BP), a
rice blast recognition method was proposed to solve the problems of low accuracy …

Rice disease recognition is crucial in automated rice disease diagnosis systems. At present,
deep convolutional neural network (CNN) is generally considered the state-of-the-art …

Bangladesh is one of the top five rice-producing and consuming countries in the world. Its
economy dramatically depends on rice-producing. Rice leaf disease is the biggest problem …

Rice leaf infections are a common hazard to rice production, affecting many farmers all over
the world. Early detection and treatment of rice leaf infection are critical for promoting healthy …

Nowadays the grain food demand is increasing due to population increase. Rice is one of
the essential foods for half of the world's population. In India most of the farmer struggled to …

Background Diverse modeling approaches viz. neural networks and multiple regression
have been followed to date for disease prediction in plant populations. However, due to their …

Rice blast is considered as the most destructive disease that threatens global rice
production and causes severe economic losses worldwide. A detection of rice blast infection …