Globally, all the major crops are significantly affected by diseases every year, as manual
inspection across diverse fields is time-consuming, tedious, and requires expert knowledge …

Plant pests and diseases are a significant threat to almost all major types of plants and
global food security. Traditional inspection across different plant fields is time-consuming …

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 …

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 …

Corn disease prediction is an essential part of agricultural productivity. This paper presents
a novel 3D-dense convolutional neural network (3D-DCNN) optimized using the Ebola …

Recent technological developments in the primary sector and machine learning algorithms
allow the combined application of many promising solutions in precision agriculture. For …

Plant diseases can significantly impact agricultural productivity if not promptly identified and
treated. Traditional plant disease classification methods are often challenging and time …

A farmer faces several challenges associated with fruit rot disease in the areca nut crop.
Weather factors, including rainfall and temperature, largely influence the disease severity …

Simple Summary This paper is mainly based on the tea disease leaves for image
classification research, using a combination of convolution, iterative module and transformer …