論文解析《Deep Convolutional Neural Network Features and the Original Image》
這一篇論文詳細分析了人臉識別中CNN網絡提取到的features有一些什麼樣的性質，通常人臉識別中CNN出來後面接一個線性層用交叉熵來分類，這裏的features值得就是cnn出來的512或者128維的浮點數組。數據庫 文章首先用這個features做爲輸入，使用LDA來分類，預測頭部姿態Yaw,Pitch，和圖像媒介，獲得下面的結果，能夠看到，embeding features仍是包含反映面部姿
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相關文章
- 1. 論文解析《Deep Convolutional Neural Network Features and the Original Image》
- 2. Identifying drug–target interactions based on graph convolutional network and deep neural network 論文
- 3. Deep Convolutional Neural Network Architecture
- 4. 總結Deep Convolutional Neural Network for Image Deconvolution
- 5. Stereoscopic image quality assessment by deep convolutional neural network
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- 10. A new deep convolutional neural network for fast hyperspectral image classification Review