摘要
In the last decade, deep learning has attracted much attention and becomes a dominant technology in artificial intelligence community. This chapter reviews the concepts, methods, and latest applications of deep learning. Firstly, the basic concepts and developing history of deep learning are revisited briefly. Then, five basic types of deep learning methods, i.e., stacked autoencoders, deep belief networks, convolutional neural networks, recurrent neural networks, and generative adversarial networks, are introduced according to applications of deep learning in other domains that are briefly illustrated based on the types of data, such as acoustic data, image data, and textual data. Finally, several issues facing by deep learning are discussed to conclude the trends.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Deep Learning in Object Detection and Recognition |
| 出版商 | Springer Singapore |
| 页 | 1-18 |
| 页数 | 18 |
| ISBN(电子版) | 9789811051524 |
| ISBN(印刷版) | 9789811051517 |
| DOI | |
| 出版状态 | 已出版 - 1 1月 2019 |
学术指纹
探究 'An overview of deep learning' 的科研主题。它们共同构成独一无二的学术指纹。引用此
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