September 19, 2025WaterOpen Access

A2DSC-Net: A Network Based on Multi-Branch Dilated and Dynamic Snake Convolutions for Water Body Extraction

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A2DSC-Net shows enhanced recall and precision in water body extraction, highlighting its dual-module design.

A2DSC-Net achieves an average precision of 96.34%, addressing the loss of small water body features effectively.
The model integrates both multi-branch dilated convolution and dynamic snake convolution for improved accuracy.
Ablation studies demonstrate that the model outperforms classical segmentation models like U-Net and DeepLabv3+.
The innovative design enhances water body delineation in complex backgrounds, proving its reliability.

Zhang et al. (2025) studied this question.

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