Plant Disease Classification Using an Ensemble Learning Model of Convolutional Neural Networks and Vision Transformers

The main objectives of this project are to classify plant diseases accurately using an ensemble model combining Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). It leverages the strengths of both architectures to enhance feature extraction and improve classification performance on leaf image datasets. This method contributes to early disease detection, supporting timely intervention and better crop management in agriculture.