Under changing climate and burgeoning food production demands, climate-smart
agriculture (CSA) practices are the need of the hour. Physically-based crop models have …

The agricultural sector plays a key role in supplying quality food and makes the greatest
contribution to growing economies and populations. Plant disease may cause significant …

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 …

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 …

In this paper, we proposed a convolutional neural network based on Inception and residual
structure with an embedded modified convolutional block attention module (CBAM), aiming …

Plant-leaf disease detection is one of the key problems of smart agriculture which has a
significant impact on the global economy. To mitigate this, intelligent agricultural solutions …

Plant diseases have recently increased and exacerbated due to several factors such as
climate change, chemicals' misuse and pollution. They represent a severe threat for both …

Automation in the agricultural field is a requirement of all the countries. Usually, plant
diseases are observed in the form of visual symptoms and many deep learning-based …

Accurate identification of crop diseases is an effective way to promote the development of
intelligent and modernized agricultural production, as well as to reduce the use of pesticides …

Plant diseases and pests have always been major contributors to losses that occur in
agriculture. Currently, the use of deep learning-based convolutional neural network models …