- Hands-On Generative Adversarial Networks with Keras
- Rafael Valle
- 106字
- 2021-06-24 14:33:51
A fully connected layer
Feedforward neural networks have this name because the flow of information being evaluated by the neural network starts at the input , flows all the way through the hidden layers, and finally reaches the output
. Note that the output of each layer does flow back to itself. In some models there are residual connections in which the input of the layer is added or concatenated to the output of the layer itself. In the following figure, we provide a visualization in which the input of Layer 2, Out 1, is concatenated with the output of Layer 2:

推薦閱讀
- 一本書玩轉(zhuǎn)數(shù)據(jù)分析(雙色圖解版)
- Dreamweaver CS3網(wǎng)頁設計50例
- Learning Apache Cassandra(Second Edition)
- 自動檢測與轉(zhuǎn)換技術(shù)
- Maya極速引擎:材質(zhì)篇
- Windows環(huán)境下32位匯編語言程序設計
- Linux:Powerful Server Administration
- 分數(shù)階系統(tǒng)分析與控制研究
- 大數(shù)據(jù)案例精析
- 電腦上網(wǎng)入門
- 寒江獨釣:Windows內(nèi)核安全編程
- 基于人工免疫原理的檢測系統(tǒng)模型及其應用
- 計算機硬件技術(shù)基礎(第2版)
- 機器人剛?cè)狁詈蟿恿W
- 天才與算法:人腦與AI的數(shù)學思維