🌿 Research Focus
Designing deep learning models for crop leaf disease detection and classification. Also developing a novel SoyLeaf dataset in collaboration with ICAR-NSRI Indore — providing a rich, real-world benchmark for soybean leaf disease research. The work bridges precision agriculture and deep learning to enable scalable, accurate automated disease diagnosis in the field.
Research Details
Developing Deep Learning Models for Crop Leaf Disease Detection and Classification
Published Papers (1 SCI)
Crop Leaf Disease Detection
Deep learning architectures for automated detection and localisation of diseases in crop leaf imagery.
SoyLeaf Dataset Development
Creating a novel real-world soybean leaf disease dataset with ICAR-NSRI Indore — a key contribution to the field.
Data Preprocessing
Novel preprocessing pipelines for real-life agricultural image datasets to improve model generalisation.
Precision Agriculture
Scalable AI tools for field-deployable crop disease monitoring supporting precision breeding programmes.
Keywords
Education
Technical Skills
Programming
Tools