Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

Study on Image Detection and Recognition based on Deep Neural Network under Cloud Computing Services

Authors
Feng Liu, Peiwei Wang, Zhixian Wang
Corresponding Author
Feng Liu
Available Online April 2017.
DOI
10.2991/emim-17.2017.281How to use a DOI?
Keywords
Image detection; Image recognition; Deep neural network; Cloud computing
Abstract

Deep learning model has the ability to extract image features independently, and also can extract abstract features. This paper studied on image detection and recognition based on deep neural network under cloud computing service. Firstly, the cloud computing service model was introduced. Secondly, the learning network was designed by the optimization method. Lastly, the test results were analyzed by recall rate and confusion Matrix, convergence performance and comparison of accuracy. The results show the deep neural network under cloud computing services is a valid method for image detection and recognition.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
10.2991/emim-17.2017.281
ISSN
2352-538X
DOI
10.2991/emim-17.2017.281How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Feng Liu
AU  - Peiwei Wang
AU  - Zhixian Wang
PY  - 2017/04
DA  - 2017/04
TI  - Study on Image Detection and Recognition based on Deep Neural Network under Cloud Computing Services
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 1406
EP  - 1409
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.281
DO  - 10.2991/emim-17.2017.281
ID  - Liu2017/04
ER  -