The detection, quantification, diagnosis, and identification of plant diseases is particularly
crucial for precision agriculture. Recently, traditional visual assessment technology has not …

Pathogen infection has greatly reduced crop production. As the symptoms of diseases
usually appear when the plants are infected severely, rapid identification approaches are …

Over the past decades, rice crops are crucially admitted as one of the powerful energy
streams for the production of resources. Rice plant diseases are considered as a raising …

Automatic diagnosis and control of rice plant disease are highly desired by agricultural
experts. Many machine learning approaches have been proposed in automating rice …

On-time recognition and early control of the stresses in the paddy crops at the booting
growth stage is the key to prevent qualitative and quantitative loss of agricultural yield. The …

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 …

Agriculture production is one of the fundamental contributors to a nation's economic
development. Every year, plant diseases result in significant crop losses that threaten the …

Over the last few decades, Fire Blight (FB) has recognized as the most dangerous diseases
of apple and pear trees in the world. Timely diagnosis is very important for the detection of …

The agriculture sector is no exception to the widespread usage of deep learning tools and
techniques. In this paper, an automated detection method on the basis of pre-trained …

In recent times, various researchers attempted to develop artificial intelligence (AI) assisted
techniques in the field of agriculture for early detection, surveillance and treatment related to …