A fine-grained dataset named iSOOD for sewage outfalls objective detection in natural environments
<p><strong>Basic Information:</strong></p> <p>The 10481 images in iSOOD were captured using UAVs and handheld cameras by individuals from the river basin in China. Our study has carefully annotated these images to ensure accuracy and consistency. The iSOOD has undergone technical validation utilizing the YOLOv5 objective detection model. The iSOOD have been publicly released after undergoing desensitization, with the goal of promoting interdisciplinary collaboration and accelerating advancements in the intelligence watershed management. We expect that the iSOOD dataset is anticipated to inspire further research on the SOs detection and the control of pollution migration paths, and serve as a fundamental resource for the use of advanced deep learning visual technology in environmental monitoring.</p> <p><strong>Usage Policy:</strong><br>If you plan to use our data in a scientific analysis paper, we strongly recommend contacting us in advance to seek opinions, and consider our contributions in the acknowledgments or as co-authors.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0
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