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Fig. 1 | BioData Mining

Fig. 1

From: Sparse self-attention aggregation networks for neural sequence slice interpolation

Fig. 1

Overview of the SSAN algorithm, which includes the siamese residual dense network, attention-aware layers, and hybrid network. Given two input EM images, we first use the RDN module to calculate the forward and reverse features and then use the proposed attention-aware layer to generate warped intermediate frames. We then use a hybrid network adaptively fusing the warped intermediate frames to generate the final intermediate frame

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