Original article was published on Artificial Intelligence on Medium
Reading: DRRN, Zhang JNCA’20 — Deep Recursive Residual Network (Semantic Segmentation)
Recursive Blocks to Improve Prediction of FCN While Reducing Parameters, Also Enhanced Mask R-CNN
In this story, Deep Recursive Residual Network for Image Semantic Segmentation (DRRN, Zhang JNCAA’20), is briefly presented. In this paper:
- DRRN for image semantic segmentation is proposed.
- Recursive blocks are introduced in Residual Block (ResNet).
- A concatenation layer is utilized to combine each output map of the recursive convolution layers at different iteration with same resolution so that different field-of-views of feature maps can be gathered.
This is a journal paper published in 2020 JNCA (Journal of Network and Computer Applications) with high impact factor of 5.273. (Sik-Ho Tsang @ Medium)