Deep learning (DL) plays an important role in modern agriculture, especially in plant
pathology using leaf images where convolutional neural networks (CNN) are attracting a lot …

Crop-borne illnesses are more resistant and frequent. Thus, producers face a problem that
impacts net productivity. If plant illnesses could be detected early and warned to farmers, this …

Plant diseases lower crop quality and quantity, making them crucial. Thus, early disease
identification and diagnosis are essential. To automate Maize leaf disease classification, we …

The destructive disease known as cotton leaf bacterial blight is a major danger to cotton
crops all over the world. To effectively manage crops and maintain yields, early and precise …

The cotton leaf disease detection model combines Convolutional Neural Networks (CNN)
with Explainable artificial intelligence (XAI) technology for the goal of diagnosing diseases in …

For efficient disease control and long-term cotton production, cotton leaf disease prediction
must be precise and timely. Convolutional neural networks (CNNs), in particular, have …

Precision agriculture aims to improve agricultural productivity by combining technology and
farming. The productivity of the cotton is mostly effected by leaf diseases, if we predict these …