Abstract: Graph neural network (GNN) models are capable of capturing the intrinsic structure and semantic relationships within data and this mechanism grants them substantial potential advantages in ...
In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...
Abstract: Graph convolutional network (GCN) combined with convolutional neural network (CNN) exhibits significant potential in hyperspectral image (HSI) classification. Hypergraph convolutional ...
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