Saved in:
| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2026
|
| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.20176021 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- <p><strong>OpenField-BD-Tomato-Maturity-Detection</strong> is an object detection dataset developed for tomato maturity identification under natural open-field conditions in Bangladesh. The dataset contains <strong>600 tomato field images</strong> with annotated tomato objects belonging to three maturity classes: <strong>green</strong>, <strong>half-ripe</strong>, and <strong>fully-ripe</strong>.</p> <p>The images were collected from real tomato cultivation fields, where natural variations such as sunlight, shadow, complex background, leaf occlusion, fruit position, and different viewing angles are present. These field-level variations make the dataset suitable for developing and evaluating tomato detection models for practical agricultural applications.</p> <p>This dataset can be used for tomato maturity detection, ripeness monitoring, precision agriculture, smart farming, automated harvesting support, and computer vision-based crop analysis.</p>