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.
CITATION STYLE
Xia, Z. (2019). An overview of deep learning. In Deep Learning in Object Detection and Recognition (pp. 1–18). Springer Singapore. https://doi.org/10.1007/978-981-10-5152-4_1
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