Residual network with dense block

Tianzhong Song; Yan Song; Yongxiong Wang; Xuegang Huang

doi:10.1117/1.JEI.27.5.053036

11 October 2018 Residual network with dense block

Tianzhong Song, Yan Song, Yongxiong Wang, Xuegang Huang

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 5, 053036 (October 2018). https://doi.org/10.1117/1.JEI.27.5.053036

Abstract

We propose a residual network with dense block (RNDB) to obtain a higher performance over the original residual network (ResNet). In the designed RNDB, a small dense block in the basic architecture of the residual block is introduced to enhance the feature mapping. As such, the application of the dense block helps the underlying ResNet adequately use the feature maps with dense connections. Thus, the optimization ability of the RNDBs is significantly promoted. In addition, the dense block is adopted in the variants of ResNet such as the residual networks of residual networks (RoR) and wide residual network (WRN) to further improve their performances. Finally, the experiments are utilized to demonstrate the validity of the employment of the dense block to the ResNets, RoRs, and WRNs, where the state-of-the-art result is effectively achieved on CIFAR-10 compared to the original ResNets, RoRs, and WRNs, respectively.

Citation Download Citation

Tianzhong Song, Yan Song, Yongxiong Wang, and Xuegang Huang "Residual network with dense block," Journal of Electronic Imaging 27(5), 053036 (11 October 2018). https://doi.org/10.1117/1.JEI.27.5.053036

Received: 28 March 2018; Accepted: 14 September 2018; Published: 11 October 2018

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