Deep Learning in Visual Computing and Signal Processing
Joint Authors
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-02-19
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
Deep learning is a subfield of machine learning, which aims to learn a hierarchy of features from input data.
Nowadays, researchers have intensively investigated deep learning algorithms for solving challenging problems in many areas such as image classification, speech recognition, signal processing, and natural language processing.
In this study, we not only review typical deep learning algorithms in computer vision and signal processing but also provide detailed information on how to apply deep learning to specific areas such as road crack detection, fault diagnosis, and human activity detection.
Besides, this study also discusses the challenges of designing and training deep neural networks.
American Psychological Association (APA)
Xie, Danfeng& Zhang, Lei& Bai, Li. 2017. Deep Learning in Visual Computing and Signal Processing. Applied Computational Intelligence and Soft Computing،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1121412
Modern Language Association (MLA)
Xie, Danfeng…[et al.]. Deep Learning in Visual Computing and Signal Processing. Applied Computational Intelligence and Soft Computing No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1121412
American Medical Association (AMA)
Xie, Danfeng& Zhang, Lei& Bai, Li. Deep Learning in Visual Computing and Signal Processing. Applied Computational Intelligence and Soft Computing. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1121412
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121412