ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression 1. 架構 在給定預先訓練的模型的情況下，將以預定義的壓縮率逐層修剪該模型。框架總體如下： 濾波器選擇。如果我們能用第 ( i + 1 ) (i+1) (i+1)層輸入中的一個通道子集來近似第 i + 1 i+1 i+1層的輸出，可以將 ( i + 1
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相關文章
- 1. ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression 閱讀筆記
- 2. 【ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression】論文筆記
- 3. ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression筆記
- 4. Reading Note: ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression
- 5. 論文筆記——ThiNet: A Filter Level Pruning Method for Deep Neural Network Compreesion
- 6. 【論文閱讀筆記】Deep Neural Network Compression with Single and Multiple Level Quantization
- 7. An Entropy-based Pruning Method for CNN Compression
- 8. Channel Pruning for Accelerating Very Deep Neural Networks
- 9. 2018-22Deep Compression: Compression Deep Neural Networks With Pruning, Trained Quantization And...
- 10. Deep Compression : Compressing Deep Neual Networks With Pruning, Trained Quantization And Huffman Co