Recurrent Neural Networks
CRF-RNN
Introduced by Zheng et al. in Conditional Random Fields as Recurrent Neural NetworksCRF-RNN is a formulation of a CRF as a Recurrent Neural Network. Specifically it formulates mean-field approximate inference for the Conditional Random Fields with Gaussian pairwise potentials as Recurrent Neural Networks.
Source: Conditional Random Fields as Recurrent Neural Networks
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Semantic Segmentation | 3 | 37.50% |
| Image Segmentation | 2 | 25.00% |
| Brain Tumor Segmentation | 1 | 12.50% |
| Tumor Segmentation | 1 | 12.50% |
| Real-Time Semantic Segmentation | 1 | 12.50% |
Softmax
