January 2019
Beginner to intermediate
576 pages
14h 31m
Chinese
Content preview from 深度學習｜內行人的做法
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遞歸神經網路
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171
紅色花束
平板
一瓶水
裝有冰塊和檸檬的一杯水
一杯咖啡
餐桌上擺放著一些早餐
一盤水果
香蕉切片
叉子
一個人坐在桌前
圖 4-28 混合使用 CNN/RNN 來標記圖片
38
實際上，這類網路是混合使用 CNN 與 BRNN（雙向遞迴神經網路）所組合起來的
結果。
遞歸神經網路
遞歸神經網路（Recursive Neural Networks）就像 RNN 一樣，可處理非固定長度的輸
入。主要的區別在於，遞歸神經網路有能力把訓練組資料中的分層結構（hierarchial
structures）模型化。舉例來說，一般圖片通常是由許多物體所組成的一個場景。場景的
解構不只重要，而且通常是很有趣的問題。這種解構天生具有遞歸的性質，而我們的挑
戰在於，不僅要識別出場景中的物體，還要識別出物體與場景之間有什麼關係。
38 圖片來自 Karpathy 與 Fei-Fei（李飛飛）於 2014 年發表的「用於生成圖片描述的深度視覺語義對齊
（Deep Visual-Semantic Alignments for Generating Image Descriptions，https://arxiv.org/abs/1412.2306v2）」
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.