Plant Disease Detection Using Image Processing and Machine Learning
This addresses the labor-intensive and time-consuming task of disease detection in agriculture, though it appears incremental as it applies existing methods to a specific domain.
The paper tackled the problem of detecting crop diseases by proposing a system that uses computer vision and machine learning, achieving 93% accuracy in identifying 20 different diseases across 5 common plants.
One of the important and tedious task in agricultural practices is the detection of the disease on crops. It requires huge time as well as skilled labor. This paper proposes a smart and efficient technique for detection of crop disease which uses computer vision and machine learning techniques. The proposed system is able to detect 20 different diseases of 5 common plants with 93% accuracy.