Abstract:Crop diseases are a major cause of reduced productivity in India, with farmers often struggling to identify and control them. Consequently, the development of advanced techniques for early disease detection is crucial for minimizing losses. This study investigates the performance of various Machine Learning (ML) algorithms, including Random Forest (RF), AdaBoost, Gradient Boosting (GB), and Multi-Layer Perceptron (MLP), for predicting diseases in chili crops based on images. The primary objective is to identif… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.