ArminMoghimi/Fine-tune-the-Segment-Anything-Model-SAM-

A. Moghimi, M. Welzel, T. Celik, and T. Schlurmann, "A Comparative Performance Analysis of Popular Deep Learning Models and Segment Anything Model (SAM) for River Water Segmentation in Close-Range Remote Sensing Imagery,"

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Emerging

This tool helps hydrologists and environmental researchers precisely identify river water in aerial or drone imagery. By taking close-range remote sensing images as input, it produces segmented images that clearly delineate river areas, making it easier to monitor waterways or assess environmental changes. This is designed for practitioners who need accurate, automated water body detection.

No commits in the last 6 months.

Use this if you need to accurately and efficiently segment river water from close-range remote sensing imagery, especially for environmental monitoring or hydrological studies.

Not ideal if your primary goal is general object detection or if you are working with satellite imagery at a much broader scale, as it's optimized for fine-grained river water segmentation from close-range captures.

hydrology environmental-monitoring remote-sensing waterway-analysis image-segmentation
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 8 / 25
Community 17 / 25

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Last pushed

Dec 30, 2024

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