To address the above problems, a liver segmentation network based on multi- scale semantic features fusion and attention mechanism (MSFA-Net) is proposed. Firstly, dilated residual convolution (DRC) is used to capture multi-scale features. Then, the MSFA module combines top-down and bottom...
Under the same conditions, it can be intuitively found that the MSFA-Net model has high accuracy and is more suitable for semantic segmentation of point clouds of historical buildings by comparing the MSFA-Net model with other semantic segmentation models. In addition, this article also conducted ...
Based on this, this paper proposes a unique semantic segmentation network design called MSFA-Net. To obtain multiscale features and suppress irrelevant information, a double attention aggregation module is first introduced. Then, to enhance the model's robustness and generalization capabilities, a ...