Classification and Identification of Plant Leaf Disease Leveraging Advanced Machine Learning and Deep Learning Techniques - Harshita Bhati (International Journal of Intelligent Systems and Applications in Engineering, 2024)
In India and globally, agriculture is very important in human life, as it is essential for providing food and promoting economic growth. Yet, plant leaves and crops could be infected by several diseases that impair their growth and cause a notable decline in agricultural productivity. Therefore, recognition of these diseases should be made in early time to avoid further damage. The traditional methods to predict and classify plant leaf diseases have always been very tiresome and faulty. Manual detection may cause delays, leading to significant crop losses and low yields. Computer vision technology is a proven enabler, which helps farmers to reduce their damage and increase production. There are multiple ways to detect and classify infections in plants using their images. Although much progress has been made, researchers must continuously improve their work to accommodate new challenges and incorporate the latest advancements. In this paper, we are focusing on advanced machine learning technology which has helped with improving the classification. Our review has shown that machine learning along with transfer learning has proven to be an efficient solution. The paper then analyses the main issues that need to be examined to enable further growth and improvement, such as image dataset formation, big data auxiliary domain, and optimization.