Images-based Plant Pest Detection Using Deep Learning Model

Images-based Plant Pest Detection Using Deep Learning Model

Authors- Gaurav Samdani, Rishipal Bansode, Michael Braham

Abstract-The use of artificial intelligence (AI) and machine learning (ML) in agricultural applications has gained significant attention in recent years due to its potential to revolutionize farming practices and enhance food security. One such area of research is the development of AI-powered systems for the early detection and diagnosis of crop diseases. Detecting diseases in crops at an early stage is crucial for farmers to implement timely interventions and prevent significant yield losses.According to the Food and Agriculture Organization (FAO) of the United Nations, plant diseases are responsible for substantial crop losses worldwide, with estimates suggesting that up to 40% of global crop production is lost annually due to pests and diseases (FAO, 2019). Traditional methods of disease detection often rely on visual inspection by farmers, which can be time-consuming, subjective, and prone to errors. In contrast, AI-based approaches offer the potential for automated, accurate, and rapid identification of crop diseases using image analysis techniques

DOI: /10.61463/ijset.vol.13.issue1.117