Datasets
Project 1: AI-based Rice Leaf Disease Identification Enhanced by Dynamic Mode Decomposition.
Dataset Description
The dataset comprises 3,416 rice leaf images collected from various sources, including Kaggle and agricultural databases. It features images of four rice leaf diseases: bacterial blight, brown spot, blast, Tungro, as well as healthy variants. The images were resized to 224 × 224 pixels. A subset of 300 images was reserved for testing, and 550 images were designated for validation.
Project 2: Improved Bacterial Leaf Blight Severity Progression Analysis in Rice Using Enhanced Segmentation and Deep Learning.
Dataset Description
Disease samples were collected from fields in Palakkad and Thrissur districts of Kerala by trained personnel from the Department of Plant Pathology, College of Agriculture, Vellanikkara. The samples were selected to include bacterial leaf diseases of interest. Severity classification was performed on a 0-7 scale with guidance from agricultural experts at the College of Agriculture, Padannakkad. This systematic framework categorizes severity into discrete stages, allowing for effective analysis and comparison of disease progression across samples and conditions.
