神經網絡後處理：A Convolutional Neural Network Approach for Post-Processing in HEVC Intra Coding
AR-CNN（Artifact reduction） ：只適用於JPEG壓縮 四層全卷積層，沒有pooling和全連接層，輸入和輸出是相同size。網絡結構如下： g()是非線性mapping函數，在AR-CNN中是ReLU函數，即 g ( x ) = m a x ( 0 , x ) g(x)=max\left ( 0,x \right ) g(x)=max(0,x)。AR-CNN的配置如下圖所示
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相關文章
- 1. 神經網絡後處理：A PRACTICAL CONVOLUTIONAL NEURAL NETWORK AS LOOP FILTER FOR INTRA FRAME
- 2. 【論文筆記】(HEVC)《Multi-stage Attention Convolutional Neural Networks for HEVC In-Loop Filtering》
- 3. 卷積神經網絡（Convolutional Neural Network）
- 4. Convolutional Neural Network 卷積神經網絡
- 5. 卷積神經網絡（Convolutional Neural Network, CNN）
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- 7. A Convolutional Neural Network Approach for Half-Pel Interpolation in Video Coding一視頻編碼中半像素插值的卷積神經網絡
- 8. 神經網絡一（Neural Network）
- 9. 【網絡架構】Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
- 10. A perceptual quantization strategy for HEVC based on a convolutional neural network trained on natur