U-LBMNet

U-LBMNet is a U-shaped neural network architecture that integrates the principles of the Lattice Boltzmann Method into an encoder–decoder framework for dense image prediction tasks. By replacing conventional feature extraction with LBM streaming, collision, and moment operations, the network efficiently learns hierarchical multi-scale representations while preserving fine spatial details through skip connections. Its physics-inspired design provides an interpretable, scalable, and computationally efficient solution for semantic segmentation, medical image analysis, and other pixel-level computer vision applications.