Crop production can be greatly reduced due to various diseases, which seriously endangers
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …

In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

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 diseases are considered one of the main factors influencing food production and
minimize losses in production, and it is essential that crop diseases have fast detection and …

Improvement of deep learning algorithms in smart agriculture is important to support the
early detection of plant diseases, thereby improving crop yields. Data acquisition for …

In precision agriculture, the accurate segmentation of crops and weeds in agronomic images
has always been the center of attention. Many methods have been proposed but still the …

Residential energy consumption data and related sociodemographic information are critical
for energy demand management, including providing personalized services, ensuring …

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 …

Precision agriculture is considered to be a fundamental approach in pursuing a low-input,
high-efficiency, and sustainable kind of agriculture when performing site-specific …

The use of deep networks in agriculture has increased enormously in the last decade
including their use to classify different plant leaf stresses. More recently, a large number of …