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About Remote Sensing: Fully Convolutional Neural Network For Rapid Flood Segmentation in Synthetic Aperture Radar Imagery
1. The document discusses using a fully convolutional neural network (CNN) for rapid flood segmentation in synthetic aperture radar (SAR) imagery. 2. Traditional flood mapping methods using optical imagery are limited by cloud cover and daylight requirements. SAR imagery provides an alternative as it can be taken regardless of weather conditions. 3. The authors design a CNN model trained on flood masks generated from classical techniques and manual cleaning. Their method reduces flood mapping time by 80% while achieving strong performance across different locations and environments.
Detailed Information
| Author: | ['Paulianne Fontoura'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 30 |
| Language: | English |
| Format: | |
| Price: | FREE |
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