Artificial Intelligence for disease identification is currently the focus of great research interest.
Nonetheless, the approach has some problems, for example, identification takes a long time …

Apple leaf diseases seriously damage the yield and quality of apples. Current apple leaf
disease diagnosis methods primarily rely on human visual inspection, which often results in …

Object detection and classification denotes one of the most extensively-utilized machine
vision applications given the high requirements put forward for object classification and …

The main motive of this project is “to create a website for the farmers to get a better crop,
fertilizer recommendation, and plant disease prediction”. The Open Weather API is used to …

Apple foliar diseases are a group of diseases that affect the leaves of apple trees. These
diseases can significantly impact apple tree health and fruit yield. Ordinary apple foliar …

Apple leaf diseases are one of the most important factors that reduce apple quality and yield.
The object detection technology based on deep learning can detect diseases in a timely …

Cotton is an important cash crop. Cotton diseases have a considerable adverse influence on
cotton yield and quality. Timely and accurate identification of cotton disease types is …

This paper investigates the usage of machine learning (ML) algorithms on agricultural
images with the aim of extracting information regarding the health of plants. More …

In agriculture, leaf diseases often appear in changing weather conditions. Changing
weather conditions can be very rainy or very hot or very humid. These factors make plants …

Rice sheath blight is one of the main diseases in rice production. The traditional detection
method, which needs manual recognition, is usually inefficient and slow. In this study, a …