Access the full text.
Sign up today, get DeepDyve free for 14 days.
Liang Chen, N. Tokuda, A. Nagai (2007)
Capacity analysis for a two-level decoupled Hamming network for associative memory under a noisy environmentNeural networks : the official journal of the International Neural Network Society, 20 5
A. Pentland, B. Moghaddam, Thad Starner (1994)
View-based and modular eigenspaces for face recognition1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
Peng Wang, Lam Tran, Q. Ji (2006)
Improving Face Recognition by Online Image Alignment18th International Conference on Pattern Recognition (ICPR'06), 1
D. Keren (2003)
Recognizing image "style" and activities in video using local features and naive BayesPattern Recognit. Lett., 24
Peng Wang, Matthew Green, Q. Ji, J. Wayman (2005)
Automatic Eye Detection and Its Validation2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops
N. Ikeda, P. Watta, Metin Artiklar, M. Hassoun (2001)
A two-level Hamming network for high performance associative memoryNeural networks : the official journal of the International Neural Network Society, 14 9
B. Julsing (2007)
Face Recognition with Local Binary Patterns
Christopher Bishop (2006)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Liang Chen, N. Tokuda (2000)
Robustness of Regional Matching Scheme over Global Matching SchemeArXiv, cs.CV/0005001
Deng Cai, Xiaofei He, Yuxiao Hu, Jiawei Han, Thomas Huang (2007)
Learning a Spatially Smooth Subspace for Face Recognition2007 IEEE Conference on Computer Vision and Pattern Recognition
Liang Chen, N. Tokuda (2005)
A general stability analysis on regional and national voting schemes against noise - why is an electoral college more stable than a direct popular election?Artif. Intell., 163
Conrad Sanderson, K. Paliwal (2003)
Fast features for face authentication under illumination direction changesPattern Recognit. Lett., 24
Xiaogang Wang, Xiaoou Tang (2004)
A unified framework for subspace face recognitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 26
Liang Chen, N. Tokuda (2003)
Stability Analysis of Regional and National Voting Schemes by a Continuous ModelIEEE Trans. Knowl. Data Eng., 15
Deng Cai, Xiaofei He, Jiawei Han (2008)
SRDA: An Efficient Algorithm for Large-Scale Discriminant AnalysisIEEE Transactions on Knowledge and Data Engineering, 20
Radford Neal (2006)
Pattern Recognition and Machine LearningPattern Recognition and Machine Learning
Reconstructing the challenging human face identification process as a stability problem, we show that Electoral College can be used as a framework that provides a significantly enhanced face identification process by improving the accuracy of all holistic algorithms. The results are demonstrated by extensive experiments on benchmark face databases applying the Electoral College framework embedded with standard baseline and newly developed face identification algorithms.
Artificial Intelligence Review – Springer Journals
Published: Oct 29, 2009
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.