【Pruning系列：一】Learning Efficient Convolutional Networks through Network Slimming
NS 機構 Tsinghua,Intel motivation 訓練中的剪枝 基於BN（Batch Normalization）層的廣泛使用，在BN層加入channel-wise scaling factor 並對之加L1 regularizer使之稀疏，然後裁剪scaling factor值小的部分對應權重 用 BN 層的 y 來表示卷積核的重要程度，y 小對應卷積核重要性低 γ 非常小時，送入
相關文章
- 1. 模型壓縮：Networks Slimming-Learning Efficient Convolutional Networks through Network Slimming
- 2. 【Pruning系列：二】Learning Efficient Convolutional Networks through Network Slimming｜YOLOv3實踐 ｜Pytorch 總結
- 3. 模型壓縮之Learning Efficient Convolutional Networks through Network Slimming
- 4. 《Learning Efficient Convolutional Networks through Network Slimming》論文筆記
- 5. 【論文閱讀筆記】Learning Efficient Convolutional Networks through Network Slimming
- 6. DL經典文章翻譯2：Learning Efficient Convolutional Networks through Network Slimming
- 7. [論文理解] Learning Efficient Convolutional Networks through Network Slimming
- 8. 模型剪枝----Learning Efficient Convolutional Networks through Network Slimming
- 9. Pruning Convolutional Neural Networks For Resource Efficient Inference
- 10. Designing Energy-Efficient Convolutional Neural Networks using Energy-Aware Pruning
- 更多相關文章...
- • Hibernate一對多映射關係 - Hibernate教程
- • Scala List(列表) - Scala教程
- • Docker容器實戰(七) - 容器眼光下的文件系統
- • RxJava操作符（一）Creating Observables
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
- 1. Duang!超快Wi-Fi來襲
- 2. 機器學習-補充03 神經網絡之**函數(Activation Function)
- 3. git上開源maven項目部署 多module maven項目（多module maven+redis+tomcat+mysql）後臺部署流程學習記錄
- 4. ecliple-tomcat部署maven項目方式之一
- 5. eclipse新導入的項目經常可以看到「XX cannot be resolved to a type」的報錯信息
- 6. Spark RDD的依賴於DAG的工作原理
- 7. VMware安裝CentOS-8教程詳解
- 8. YDOOK：Java 項目 Spring 項目導入基本四大 jar 包 導入依賴，怎樣在 IDEA 的項目結構中導入 jar 包 導入依賴
- 9. 簡單方法使得putty（windows10上）可以免密登錄樹莓派
- 10. idea怎麼用本地maven
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. 模型壓縮：Networks Slimming-Learning Efficient Convolutional Networks through Network Slimming
- 2. 【Pruning系列：二】Learning Efficient Convolutional Networks through Network Slimming｜YOLOv3實踐 ｜Pytorch 總結
- 3. 模型壓縮之Learning Efficient Convolutional Networks through Network Slimming
- 4. 《Learning Efficient Convolutional Networks through Network Slimming》論文筆記
- 5. 【論文閱讀筆記】Learning Efficient Convolutional Networks through Network Slimming
- 6. DL經典文章翻譯2：Learning Efficient Convolutional Networks through Network Slimming
- 7. [論文理解] Learning Efficient Convolutional Networks through Network Slimming
- 8. 模型剪枝----Learning Efficient Convolutional Networks through Network Slimming
- 9. Pruning Convolutional Neural Networks For Resource Efficient Inference
- 10. Designing Energy-Efficient Convolutional Neural Networks using Energy-Aware Pruning