Authors : Bhagyashree Bais
DOI : 10.46335/IJIES.2024.9.9.3
Abstract— Invasive organisms and Plant disorder have a big influence on output and quality. By employing digital image processing, scholars can precisely detect these problems. Researchers are looking into using deep learning to identify pests and agricultural diseases since recent developments in the field have outperformed more conventional approaches. This paper provides an overview of the issue, contrasts deep learning with traditional approaches, and summarizes current work on segmentation, detection, and classification networks. Performance assessments and common datasets are addressed. Research directions and possible answers are discussed, as well as challenges in practical application. The paper concludes with a summary of upcoming developments in deep learning-based agricultural disease and pest detection. The process of detecting agricultural diseases entails locating illnesses in crops. There are two phases to it: feature extraction for picture analysis and classification, and segmentation to identify impacted regions.
