Application and Optimization of Image Fuzzy Control Algorithm based on Gaussian Blur in TensorFlow Training

DOI

10.2991/icmeit-19.2019.137How to use a DOI?

Keywords

TensorFlow, Gaussian fuzzy algorithm, the convolutional neural network, the fuzzy control algorithm.

Abstract

When training a convolutional neural network that can interpret picture ambiguity, a large number of pictures with different ambiguities are needed as a training set. This paper introduces a method to adjust the image ambiguity by adjusting the parameters in the Gaussian fuzzy algorithm. Finally, the convolutional neural network training based on TensorFlow migration learning is completed, and the ambiguity judgment of the image is realized, and the optimization effect of the fuzzy control algorithm is verified.

Copyright

© 2019, 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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TY  - CONF
AU  - Yongjun Zhang
AU  - Feiyang Ma
PY  - 2019/04
DA  - 2019/04
TI  - Application and Optimization of Image Fuzzy Control Algorithm based on Gaussian Blur in TensorFlow Training
BT  - Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SP  - 854
EP  - 860
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.137
DO  - 10.2991/icmeit-19.2019.137
ID  - Zhang2019/04
ER  -