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部分選譯Perceptual losses for real-time style transfer and super-resolution.
時間 2021-01-07
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3.方法 就像圖二顯示的,我們的系統由兩部分組成:一個圖像轉換網絡 fW 和一個被用來定義幾個損失函數的損失網絡 ϕ 。這個圖*像轉換網絡是一個深度殘差卷積神經網絡,由權重W參數化。它將輸入圖片x轉化成使出圖片 y^ ,通過製圖函數 y^=fW(x) .每一個損失函數計算一個標量值 li(y^,yi) 測量輸出圖像 y^ 和目標圖像 yi 之間的不同。這個圖像轉化網絡使用隨機梯度下降SGD進行訓練
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相關文章
1.
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
2.
[Style Transfer]——Perceptual Losses for Real-Time Style Transfer and Super-Resolution
3.
[譯] Perceptual Losses for Real-Time Style Transfer and Super-Resolution(Stanford University)
4.
論文閱讀筆記:Perceptual Losses for Real-Time Style Transfer and Super-Resolution
5.
Perceptual Losses for Real-Time Style Transfer and Super-Resolution閱讀(一)
6.
Perceptual Losses for Real-Time Style Transfer and Super-Resolution 運行程序
7.
[論文筆記] Perceptual Losses for Real-Time Style Transfer and Super-Resolution
8.
論文解讀之Perceptual Losses for Real-Time Style Transfer and Super-Resolution
9.
Perceptual Losses for Real-Time Style Transfer and Super-Resolution閱讀(二)
10.
Faster Read: Perceptual Losses for Real-Time Style Transfer and Super-Resolution
>>更多相關文章<<