層 (深度學習)

层，或层次，是深度学习模型模型架构中的一种结构或網路拓撲，它从上一层获取信息，然后将信息传递给下一层。深度学习中有几个著名的层，即卷积神经网络中的卷积层[1]和最大池化层[2][3]。基本神经网络中的全连接层和ReLU层。循環神經網路中的RNN层[4][5][6]和自动编码器中的解卷积层等。

與新皮質層次的相異

深度學習與新皮質的分層方式有本質上的分別：深度學習的分層取決於網路拓撲，新皮質的分層取決於層內的同質性。

參見

參考文獻
  1. Habibi, Aghdam, Hamed. . Heravi, Elnaz Jahani. Cham, Switzerland. 2017-05-30. ISBN 9783319575490. OCLC 987790957.
  2. Yamaguchi, Kouichi; Sakamoto, Kenji; Akabane, Toshio; Fujimoto, Yoshiji. . First International Conference on Spoken Language Processing (ICSLP 90). Kobe, Japan. November 1990.
  3. Ciresan, Dan; Meier, Ueli; Schmidhuber, Jürgen. . 2012 IEEE Conference on Computer Vision and Pattern Recognition (New York, NY: Institute of Electrical and Electronics Engineers (IEEE)). June 2012: 3642–3649. ISBN 978-1-4673-1226-4. OCLC 812295155. arXiv:1202.2745. doi:10.1109/CVPR.2012.6248110. 已忽略未知参数|s2cid= (帮助); 已忽略未知参数|citeseerx= (帮助)
  4. Dupond, Samuel. . Annual Reviews in Control. 2019, 14: 200–230.
  5. Abiodun, Oludare Isaac; Jantan, Aman; Omolara, Abiodun Esther; Dada, Kemi Victoria; Mohamed, Nachaat Abdelatif; Arshad, Humaira. . Heliyon. 2018-11-01, 4 (11): e00938. ISSN 2405-8440. PMC 6260436. PMID 30519653. doi:10.1016/j.heliyon.2018.e00938 （英语）. 已忽略未知参数|doi-access= (帮助)
  6. Tealab, Ahmed. . Future Computing and Informatics Journal. 2018-12-01, 3 (2): 334–340. ISSN 2314-7288. doi:10.1016/j.fcij.2018.10.003 （英语）. 已忽略未知参数|doi-access= (帮助)
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