Performance Evaluation of ProThinNet23 and State-of-the-Art Deep Learning Models in Plant Leaf Disease Identification

Abstract

For sustainable development in agriculture , there is a need to develop automated systems that can identify plant leaf diseases by capturing their images directly from the field. Such systems can enhance agricultural productivity and minimize crop losses. Recent advancements in the domain of machine learning and deep learning have focused on creating powerful hybrid models for the automatic detection of plant diseases, as these approaches offer higher accuracy.