Rapid improvements in deep learning (DL) techniques have made it possible to detect and
recognize objects from images. DL approaches have recently entered various agricultural …

Plant disease detection has played a significant role in combating plant diseases that pose a
threat to global agriculture and food security. Detecting these diseases early can help …

India is a cover crop region whereby agricultural production sustains a substantial
proportion of the populace and upon which the whole Indian economy is heavily reliant. As …

This paper presents a novel Deep Learning (DL) framework for cotton plant disease
prediction based on Explainable Artificial Intelligence (XAI) and Copula entropy based-Grey …

Background The common tea tree disease known as “tea coal disease”(Neocapnodium
theae Hara) can have a negative impact on tea yield and quality. The majority of …

Accurate identification of plant diseases is a critical task in agricultural production. The
existing deep learning crop disease recognition methods require a large number of labeled …

Artificial intelligence has been incorporated into modern agriculture to increase agricultural
output and resource efficiency. Utilizing deep learning, particularly convolutional neural …

Plant disease is a major concern in agriculture field. Different pathogens are causes of plant
disease. Manual inspection sometimes can cause errors in the disease detection over large …

Plants are a big part of the ecosystem. Plants are also used by humans for various purposes.
Cotton is one of these important plants and is very critical for humans. Cotton production is …

Every nation's development depends on agriculture. The term “cash crops” refers to cotton
and other important crops. Most pathogens that significantly harm crops also impact cotton …