The main method used is analysis the correlation between the features of the same layer from the first branch and the second branch.
The main method used is analysis the correlation between the features of the same layer from the first branch and the second branch. The task of dual-source ...
Image Classification. Conference Paper. Feature Correlation Analysis of Two-Branch Convolutional Networks for Multi-Source Image Classification. September 2020.
The main method used is analysis the correlation between the features of the same layer from the first branch and the second branch. The task of dual-source ...
Dec 7, 2023 · In view of this, we propose a multi-branch deep network based on the correlation features of feature maps. Convolution-correlated features are ...
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Aug 28, 2024 · The SGFN model proposed in this paper considers image spatial correlation and label semantic correlation, while the two correlations are fused hierarchically.
This paper proposes two-branch multiscale spatial–spectral feature aggregation with a self-attention mechanism for a hyperspectral image classification model ( ...
Sep 2, 2022 · We build a new convolutional neural network (CNN) based feature extraction network to extract multi-scale features from the molecular descriptors.
In the proposed network, two-branch CNNs are implemented to efficiently extract the spectral and spatial features, respectively. The kernel sizes of the ...
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Aug 28, 2022 · We propose a novel multi-feature fusion network (MFGCN), where two different convolutional networks, ie, multi-scale GCN and multi-scale convolutional neural ...