期刊论文、会议论文

Wu, Minghu

英文

Lecture Notes on Data Engineering and Communications Technologies

2367-4512

2018

6

160-166

5th International Conference on Emerging Internetworking, Data and Web Technologies (EIDWT)

Advances in Internetworking, Data & Web Technologies

JUN 10-11, 2017

Wuhan, PEOPLES R CHINA

[Rao, Zheheng;Zeng, Chunyan;Zhao, Nan;Liu, Min;Wu, Minghu] Hubei Univ Technol, Hubei Key Lab High Efficiency Utilizat Solar Ener, Wuhan, Hubei, Peoples R China.^[Rao, Zheheng;Zeng, Chunyan;Zhao, Nan;Liu, Min;Wu, Minghu] Hubei Univ Technol, Hubei Collaborat Innovat Ctr High Efficiency Util, Wuhan 430068, Hubei, Peoples R China.^[Wang, Zhifeng] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.

Leonard Barolli<&wdkj&>Mingwu Zhang<&wdkj&>Xu An Wang

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

Springer, Cham

978-3-319-59462-0

10.1007/978-3-319-59463-7_16

This research was supported by National Natural Science Foundation of China (No. 61471162, No. 61501178, No. 61501199, No. 61601177); Program of International science and technology cooperation (2015DFA10940); Science and technology support program (R & D) project of Hubei Province (2015BAA115); PhD Research Startup Foundation of Hubei University of Technology (No. BSQD13037, No. BSQD14028); Open Foundation of Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy (HBSKFZD2015005, HBSKFTD2016002).

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This paper presents a new deep network (non – very deep network) with composite residual for handwritten character recognition. The main network design is as follows: (1) Introduces an unsupervised FCM clustering algorithm to preprocess the experimental data. (2) By exploiting a composite residual structure the multilevel shortcut connection is proposed which is more suitable for the learning of residual. (3) In order to solve the problem of overfitting and time-consuming for training the network parameters, a dropout layer is added after the ...