A perceptual quantization strategy for HEVC based on a convolutional neural network trained on natur
基於在自然圖像上訓練的卷積神經網絡的HEVC的感知量化策略 局部失真可見性和局部質量的快速預測模型可以潛在地使現代的spatiotem-porally自適應編碼方案對於實時應用是可行的。本文提出了一種基於快速卷積神經網絡的HEVC量化策略。通過對從我們改進的對比度增益控制模型導出的數據訓練的網絡預測本地僞像可見性。對比度增益控制模型在我們最近的自然場景中局部失真可見性數據庫中進行了訓練[Alam
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相關文章
- 1. Tensorflow - Implement for a Convolutional Neural Network on MNIST.
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- 3. A New Hand Segmentation Method Based on Fully Convolutional Network
- 4. Paper | Enhancing HEVC Compressed Videos with a Partition-Masked Convolutional Neural Network
- 5. 01_kaggle - Using a 3D Convolutional Neural Network on medical imaging data (CT Scans) for Kaggle
- 6. Large scale crowd analysis based on convolutional neural network
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