深度學習（六十九）darknet 實現實驗 Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffma
本文主要實驗文獻文獻《Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding》算法，在tiny-yolo coco上的壓縮效果，在darknet基礎上，編寫該算法進行壓縮實驗，結果以下：算法 原始模型大小64M：mAP=0.224 spa 訓練5
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相關文章
- 1. 【Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huff】論文筆記
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- 3. deep compression:compressing deep neural networks with pruning,trained quantization and huffman codi
- 4. Compression Deep Neural Networks With Pruning, Trained Quantization And Huffman Coding
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- 6. 【Comprssion】《Deep Compression：Compressing Deep Neural Networks with Pruning，Trained QuantizationXXX》
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- 8. 百面深度學習 | 第十六期：深度網絡壓縮
- 9. Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization
- 10. Neural Networks and Deep Learning -- Class 4: Deep Neural Networks