Deep learning model to detect shipwrecks in high-resolution BAG data. A brief summary of the item is not available. Add a brief summary about the item.
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Item created: Feb 23, 2021 Item updated: Dec 31, 2024 Number of downloads: 3,519
Description
Shipwrecks are a potential threat to the ships passing by on the surface. Marking them manually is a complex and time-consuming task. Deep learning can be used to significantly optimize and automate this task. This model can be used as-is or fine-tuned to adapt to your own data/geography.
Using the model
Follow the guide to use the model. Before using this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS.
Input
BAG data (preferrably at a cell size of 0.5m).
Output
Feature class with detected shipwrecks as polygons.
Applicable geographies
The model is expected to work for any marine geography.
Model architecture
This model uses the MaskRCNN model architecture implemented in ArcGIS API for Python.
Accuracy metrics
The model has an average precision score of 0.921 percent on our validation dataset.
Sample results
Here are a few results from the model.
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Dashboard views: Desktop
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Applicable: 2d
Size: 156.453 MB
ID: 28755e99bbde42508f22b957681a70e2
Image Count: 0
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Using tiles from a cache
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No acknowledgements.Esri
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