【論文筆記】(HEVC)《Recursive Residual Convolutional Neural NetworkBased In-Loop Filtering ..》
《Recursive Residual Convolutional Neural NetworkBased In-Loop Filtering for Intra Frames》閱讀筆記 problems 深層網絡需要考慮退化和訓練難度的問題 motivation 提出RRCNN，有利於實現深層網絡，在增強學習能力的同時而不需考慮退化問題， 遞歸使用一組權值，利用更少的參數實現好的效果。 shor
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相關文章
- 1. 【論文筆記】(HEVC)《Multi-stage Attention Convolutional Neural Networks for HEVC In-Loop Filtering》
- 2. 論文筆記：Neural Collaborative Filtering
- 3. 【論文筆記】Neural Collaborative Filtering
- 4. 論文筆記：AAAI 2020 Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional
- 5. [論文筆記] [2016] [NIPS] Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
- 6. 論文筆記：Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
- 7. 論文筆記——Factorized Convolutional Neural Networks
- 8. 論文筆記：Neural Graph Collaborative Filtering
- 9. 論文筆記：Neural Collaborative Filtering(NCF)
- 10. 【論文筆記】Neural Graph Collaborative Filtering