@inproceedings{c7037209ec01407297739995e698cf33,
title = "Picture Reconstruction Optimization Using Neural Networks",
abstract = "The multilayer perceptron (MLP), as one of neural network types, is a function of one or more predictors which minimizes the error between the inputs and target variables. In this paper, the network architecture is designed and the optimal parameters are chosen. A novel method is proposed to add polynomial features to help get better results on the accuracy of reconstruction picture. The number of epochs for training is also an important fact for time consuming which has strong relationship with the avoid overtraining algorithm. The accuracy of the reconstruction work and the size of time consuming data are examined by experimental work.",
keywords = "Multilayer perceptron, Neural network, Optimization, Picture reconstruction",
author = "Yiheng Hu and Zhihua Hu and Jin Chen",
note = "Funding Information: Acknowledgments. I would like to acknowledge the funding support of Control Theory and Control Engineering Discipline XXXPY1609 and the funding is A20NH1609B21-92. Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.; International Conference on Mechatronics and Intelligent Robotics, ICMIR 2017 ; Conference date: 20-05-2017 Through 21-05-2017",
year = "2017",
month = nov,
day = "12",
doi = "10.1007/978-3-319-65978-7_3",
language = "English",
isbn = "9783319659770",
volume = "690",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer, Cham",
pages = "15--20",
editor = "Feng Qiao and Srikanta Patnaik and John Wang",
booktitle = "Recent Developments in Mechatronics and Intelligent Robotics",
address = "Switzerland",
}