This dataset contains plant disease in five different crops in New Zealand, including kiwifruit, apple, pear, avocado, and grapevine for the paper, “A Performance-Optimized Deep Learning-based Plant Disease Detection Approach for Horticultural Crops of New Zealand” published with Open Access by IEEE Access.
The images were acquired by using Samsung Galaxy S10 plus: 12 MP f/1.5-2.4 (wide), 12 MP f/2.4 (telephoto), and 16 MP, f/2.2 (ultrawide). The images were taken at a working distance of 200-300 mm.
Locations: Auckland and Palmerston North, New Zealand.
The dataset is licensed under CC BY 4.0 license. The contents of this repository are released under an Apache 2 license.
- Training dataset (1.3 GB)
- Validation dataset (450 MB)
- Testing dataset (227 MB)
- External testing dataset (77 MB)
This repository is a part of the PhD research of Muhammad Hammad Saleem (H.Saleem@massey.ac.nz; engr.hammadsaleem@gmail.com)
In case of any query, please contact Dr. Khalid Mahmood Arif (K.Arif@massey.ac.nz), Muhammad Hammad Saleem (H.Saleem@massey.ac.nz; engr.hammadsaleem@gmail.com)