Agriculture plays a vital role in the economic growth of any country. With the increase of
population, frequent changes in climatic conditions and limited resources, it becomes a …

With increasing population, the demand for agricultural productivity is rising to meet the goal
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …

The timely identification and early prevention of crop diseases are essential for improving
production. In this paper, deep convolutional-neural-network (CNN) models are …

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 …

With limited retrieval of reserves and restricted capability in plant pathology, automation of
processes becomes essential. All over the world, farmers are struggling to prevent various …

The timely identification of plant diseases prevents the negative impact on crops.
Convolutional neural network, particularly deep learning is used widely in machine vision …

The occurrence of apple diseases has dramatically affected the quality and yield of apples.
Disease monitoring is an important measure to ensure the healthy development of the apple …

Plant disease detection is a critical issue that needs to be focused on for productive
agriculture and economy. Detecting plant disease using traditional methods is a tedious job …

Global warming due to the high concentration of anthropogenic CO2 in the atmosphere is
considered one of the world's leading challenges in the 21st century as it leads to severe …

Timely identification of plant diseases plays crucial roles in the management and decision-
making to protect the agricultural yield and quality. In this research field, there have been so …