Papaya Leaf Images
Published: 8 January 2026| Version 1 | DOI: 10.17632/3f345tdg9v.1
Contributors:
Ajahar Pathan, Description
The Dataset comprises 140 papaya leaf images, each with a resolution of 150 × 150 pixels. This dataset is suitable for conducting diverse image processing experiments and serves as a valuable resource for the development and evaluation of computational models in the field of computer vision. The dataset is classified into five major classes: Boron, Healthy, Nitrogen, Phosphorus, and Potassium. The dataset is split and distributed into a Training set with 80 images, a Validation set with 40 images, and a Testing set with 20 images. Each set of leaves in the training dataset was manually annotated and categorized with the guidance of agricultural experts
Files
Institutions
- Oriental University
Categories
Computer Vision, Convolutional Neural Network, Deep Learning