Several factors associated with disease diagnosis in plants using deep learning techniques
must be considered to develop a robust system for accurate disease management. A …

Plant diseases and pests are important factors determining the yield and quality of plants.
Plant diseases and pests identification can be carried out by means of digital image …

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

Computer vision is a field that involves making a machine “see”. This technology uses a
camera and computer instead of the human eye to identify, track and measure targets for …

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

Plant diseases and insect pests cause a significant threat to agricultural production. Early
detection and diagnosis of these diseases are critical and can reduce economic losses. The …

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 …

Accurately detecting and counting fruits during plant growth using imaging and computer
vision is of importance not only from the point of view of reducing labor intensive manual …

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 …

Anthracnose, brown spot, mites, black rot, downy mildew, and leaf blight are six common
grape leaf pests and diseases, which cause severe economic losses to the grape industry …