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Coastlines
A pre-trained coastline segmentation model based on PyTorch's FPN architecture, suitable for coastline detection tasks in remote sensing images
Downloads 16
Release Time : 8/8/2024
Model Overview
This model adopts the FPN architecture with VGG11_bn as the encoder, optimized specifically for coastline segmentation tasks, accurately identifying coastline boundaries in remote sensing images
Model Features
Pre-trained Coastline Detection
Pre-trained specifically for coastline segmentation tasks, ready for direct use in remote sensing image analysis
Advantages of FPN Architecture
Utilizes a feature pyramid network structure to capture multi-scale features of images simultaneously
Lightweight Encoder
Uses VGG11_bn as the encoder, reducing computational resource requirements while maintaining performance
Plug-and-Play
Integrated via PyTorchModelHubMixin for easy loading and usage
Model Capabilities
Remote Sensing Image Analysis
Coastline Detection
Semantic Segmentation
Geographic Information System Processing
Use Cases
Geographic Information System
Coastline Change Monitoring
Monitoring changes in coastlines over time
IoU reaches 0.798
Disaster Assessment
Assessing coastline changes after typhoons or tsunamis
Environmental Monitoring
Coastal Erosion Analysis
Analyzing the extent and trends of coastal erosion
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