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Image Super Resolution Based on Fusing Multiple Convolution Neural Networks
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
In this paper, we focus on constructing an accurate super resolution system based on multiple Convolution Neural Networks (CNNs). Each individual CNN is trained separately with different network structure. A Context-wise Network Fusion (CNF) approach is proposed to integrate the outputs of individual networks by additional convolution layers. With fine-tuning the whole fused network, the accuracy is significantly improved compared to the individual networks. We also discuss other network fusion
doi:10.1109/cvprw.2017.142
dblp:conf/cvpr/RenEL17
fatcat:shncx4lihbbz5bo3fg4q7q7z2e