This paper proposes a deep learning model that uses a combination of RGB and nIR satellite images to identify flood regions.
This paper proposes a deep learning model that uses a combination of RGB and nIR satellite images to identify flood regions. The proposed model has lower ...
Reduction deep learning model for floods recognition in satellite images ... image transform algorithms to detect landslide location in satellite images ...
Oct 20, 2023 · This study looks into how deep learning was set up to predict 2D supreme depth maps during urban flood events as accurately as possible. This ...
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Abstract. Deep Learning techniques have been increasingly used in flood management to overcome the limitations of accurate, yet slow, numerical models, ...
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This study evaluated the capability of convolutional neural network (NNET C ) and recurrent neural network (NNET R ) models for flood hazard mapping.
Apr 29, 2024 · Deep learning models encounter more difficulty in classifying pixels in these satellite images into the correct classes. Therefore, by training ...
Oct 27, 2023 · This study looks into how deep learning was set up to predict 2D supreme depth maps during urban flood events as accurately as possible. This ...
We propose a novel deep-learning-based solution that uses pairs of pre- and post-disaster satellite images to identify water-related disaster-affected regions.
Jan 27, 2024 · This study addresses the vital issue of real-time flood detection and management. It innovatively combines advanced deep learning models with Large language ...