Identification of Plant Diseases Using Imaging Processing and Machine Learning

This comprehensive review explores the most current developments in the use of image processing and machine learning methods for the diagnosis of plant diseases. After a thorough review of the literature, we critically assess the different frameworks and methods used to classify disorders affecting plants. Our study highlights the advantages and disadvantages of each approach while focusing on how accurate it is in diagnosing a wide variety of illnesses. In addition, we investigate new developments and trends in this quickly developing industry. We conclude by talking about the ongoing difficulties and suggesting some directions for further study to improve the effectiveness of plant disease detection systems.