Big Data Deep Learning: Challenges and Perspectives

Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language processing. With the sheer size of data available today, bi...

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Vydané v:IEEE access Ročník 2; s. 514 - 525
Hlavní autori: Chen, Xue-Wen, Lin, Xiaotong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Big Data
Classifier design and evaluation
Computer vision
Data processing
Deep learning
feature representation
Information analysis
Machine learning
Natural language processing
neural nets models
parallel processing
Pattern recognition
Speech recognition
ISSN:2169-3536, 2169-3536
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Popis
Shrnutí:Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language processing. With the sheer size of data available today, big data brings big opportunities and transformative potential for various sectors; on the other hand, it also presents unprecedented challenges to harnessing data and information. As the data keeps getting bigger, deep learning is coming to play a key role in providing big data predictive analytics solutions. In this paper, we provide a brief overview of deep learning, and highlight current research efforts and the challenges to big data, as well as the future trends.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2014.2325029