1 / 6

Face Recognition based on Radial Basis Function and Clustering Algorithm

Face Recognition based on Radial Basis Function and Clustering Algorithm. Yuanfeng Gao 2008/12/12. Face Recognition task. Various methods Neural Network approach: - Can recessively express many rules for face recognition and has much stronger adaptability by training networks. Part I.

honorato-mcgowan
Download Presentation

Face Recognition based on Radial Basis Function and Clustering Algorithm

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Face Recognition based on Radial Basis Function and Clustering Algorithm Yuanfeng Gao 2008/12/12

  2. Face Recognition task • Various methods • Neural Network approach: - Can recessively express many rules for face recognition and has much stronger adaptability by training networks.

  3. Part I • Radial basis function (RBF) neural networks is compared with other neural network techniques - K-means clustering algorithm - Subtractive clustering algorithm • Improve the RBF and classification accuracy

  4. Part I

  5. Part II • Recognize human faces • Accomplish experiments to apply K-means and subtractive clustering algorithm • Choosing a data base to perform the experiment.

  6. Thank you

More Related