We consider the problem of representation learning for graph data. Given images are special cases of graphs with nodes lie on 2D lattices, graph embedding tasks have a natural correspondence with ...

The innovative GM-UNet architecture employs graph neural networks to capture global dependencies, fostering a more holistic comprehension of the image. Through the incorporation of GCA, our model ...