Deep Learning in Visual Computing and Signal Processing
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 processin...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2017/1320780 |
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| _version_ | 1850159321100320768 |
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| author | Danfeng Xie Lei Zhang Li Bai |
| author_facet | Danfeng Xie Lei Zhang Li Bai |
| author_sort | Danfeng Xie |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b1a00e0aefbc4653adb1f4973b59e62e |
| institution | OA Journals |
| issn | 1687-9724 1687-9732 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-b1a00e0aefbc4653adb1f4973b59e62e2025-08-20T02:23:35ZengWileyApplied Computational Intelligence and Soft Computing1687-97241687-97322017-01-01201710.1155/2017/13207801320780Deep Learning in Visual Computing and Signal ProcessingDanfeng Xie0Lei Zhang1Li Bai2Department of Electrical and Computer Engineering, Temple University, Philadelphia, PA 19121, USADepartment of Electrical and Computer Engineering, Temple University, Philadelphia, PA 19121, USADepartment of Electrical and Computer Engineering, Temple University, Philadelphia, PA 19121, USADeep 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.http://dx.doi.org/10.1155/2017/1320780 |
| spellingShingle | Danfeng Xie Lei Zhang Li Bai Deep Learning in Visual Computing and Signal Processing Applied Computational Intelligence and Soft Computing |
| title | Deep Learning in Visual Computing and Signal Processing |
| title_full | Deep Learning in Visual Computing and Signal Processing |
| title_fullStr | Deep Learning in Visual Computing and Signal Processing |
| title_full_unstemmed | Deep Learning in Visual Computing and Signal Processing |
| title_short | Deep Learning in Visual Computing and Signal Processing |
| title_sort | deep learning in visual computing and signal processing |
| url | http://dx.doi.org/10.1155/2017/1320780 |
| work_keys_str_mv | AT danfengxie deeplearninginvisualcomputingandsignalprocessing AT leizhang deeplearninginvisualcomputingandsignalprocessing AT libai deeplearninginvisualcomputingandsignalprocessing |