A survey on deep learning and its applications
By S. Dong, Ping Wang, Khushnood Abbas. Computer Science Review, 2021
1,346 citations recorded by the source corpus.
Abstract Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary and the induction methods of deep learning. Firstly, it introduces the global development and the current situation of deep learning. Secondly, it describes the structural principle, the characteristics, and some kinds of classic models of deep learning, such as stacked auto encoder, deep belief network, deep Boltzmann machine, and convolutional neural network. Thirdly, it presents the latest developments and applications of deep learning in many fields such as speech processing, computer vision, natural language processing, and medical applications. Finally, it puts forward the problems and the future research directions of deep learning.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/3af679c9c4f727dd4e6dc69dfde22a871e85da1e
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In Artificial Intelligence
In Computer Vision and Pattern Recognition
Citations in the corpus
- Video Summarization Using Deep Neural Networks: A Survey (2021, neutral): “For an overview of the different classes of deep learning architectures, the interested reader is referred to surveys such as [68]–[70].”
- A Survey of Human-in-the-loop for Machine Learning (2021, background): “learning has seen great success in a wide variety of applications, such as natural language processing, speech recognition, medical applications, computer vision, and intelligent transportation system [1].”
- Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review (2022, background): “Deep learning (DL) is a subset of machine learning and artificial intelligence that can learn from the given data [170].”