Semi-supervised Growing Neural Gas for Face Recognition

Authors:
Shireen Mohd Zaki;Hujun Yin
Affiliations:
School of Electrical and Electronic Engineering, The University of Manchester, Manchester, United Kingdom M60 1QD;School of Electrical and Electronic Engineering, The University of Manchester, Manchester, United Kingdom M60 1QD
Venue:
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Year:
2008

Citing 3
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Neural Computing and Applications

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Abstract

In many face recognition and other classification applications, there exist unlabelled data available for training along with labelled data. The use of unlabelled data can improve the performance of the classifier. In this paper, a semi-supervised growing neural gas is proposed for such applications. The classifier is first trained on the labelled data and then gradually unlabelled data is classified and added to the training data. The proposed algorithm is demonstrated, on both artificial and real datasets, to significantly boost the classification rate with the use of unlabelled data. The improvement is particularly great when the labelled dataset is small. The algorithm is computationally simple and easy to implement.