Logeswari Govindaraj

Abstract Modern day healthcare has seen an increase in polypharmacy, which is the prescription of multiple drugs as medication to treat illnesses simultaneously. Therefore there is an increased risk of adverse drug reactions resulting from drug-drug interactions. Existing techniques in the field of pharmacovigilance suffer from many drawbacks. Many machine learning approaches using single models face difficulties in identifying complex interaction patterns.

Abstract Early and accurate disease detection is important for increasing the agricultural output, decreasing the financial costs, and ensuring food security. Traditional diagnostic procedures take much time and effort, involve the necessity of having deep expertise, and are not always suitable for large scale farming disease detection. For this purpose, the current research suggests developing an explainable lightweight CNN-based model for crop disease identification based on RGB leaf images.