The growing global population and accompanying increase in food demand has put
pressure on agriculture to produce higher yields in the face of numerous challenges …

Integrating imaging sensors and artificial intelligence (AI) have contributed to detecting plant
stress symptoms, yet data analysis remains a key challenge. Data challenges include …

Plant diseases impact extensively on agricultural production growth. It results in a price hike
on food grains and vegetables. To reduce economic loss and to predict yield loss, early …

Accurate identification of plant disease is of great significance for intelligent agriculture.
Currently, plant species, disease, and severity are considered as joint categories in most …

The artificial intelligence-assisted deep learning approach plays a significant task in
identifying diseases through a large set of plant leaf images. Thus, the major aim of the …

The automatic recognition of crop diseases based on visual perception algorithms is one of
the important research directions in the current prevention and control of crop diseases …

This article presents the application of supervised learning and image classification for the
early detection of late blight disease in potato using convolutional neural network and …

The exact and unfailing categorization of medicinal plants exceeds the capabilities of the
average individual because it necessitates in-depth subject expertise and physical detection …

A rapid expansion in the world's population needs an enormous supply of food grains to
satisfy agricultural needs. Unfortunately, crop diseases adversely impact food production …

Maize is a globally important cereal crop, however, maize leaf disease is one of the most
common and devastating diseases that afflict it. Artificial intelligence methods face …