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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chuandong Wang Yanying Yang |
| Copyright Year | 2011 |
| Description | Author affiliation: College of Computer Science & Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, Jiangsu, P. R. China (Chuandong Wang) || Department of Information and Technology, Nanjing College of Forestry Police, Nanjing 210046, Jiangsu, P. R. China (Yanying Yang) |
| Abstract | Face recognition from single training image per person is one of important challenges in appearance-based pattern recognition field. Although many existing face recognition methods have achieved success in real application, but can not be directly used to the single training image scenario. The associative memory neural networks provide a feasible strategy to address such problem. In this paper, we first briefly review the existing single training sample face recognition algorithms, and then propose a new multiple value auto-associative memory neural network by modifying evolution rule and activation function. Finally, experiments on the two publicly available face databases are provided to validate the feasibility and effectiveness of the proposed algorithm. |
| Starting Page | 4947 |
| Ending Page | 4950 |
| File Size | 325304 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424481620 |
| e-ISBN | 9781424481651 |
| DOI | 10.1109/ICECENG.2011.6057185 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-09-16 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training Associative memory Image recognition Databases Face recognition Artificial neural networks Artificial neural network Face Appearance-based pattern recognition Face recgonition |
| Content Type | Text |
| Resource Type | Article |
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