@inproceedings{19f592e1a97446df84ac21482cb8f174,
title = "FADA: An efficient dimension reduction scheme for image classification",
abstract = "This paper develops a novel and efficient dimension reduction scheme-Fast Adaptive Discriminant Analysis (FADA). FADA can find a good projection with adaptation to different sample distributions and discover the classification in the subspace with na{\"i}ve Bayes classifier. FADA overcomes the high computational cost problem of current Adaptive Discriminant Analysis (ADA) and also alleviates the overfitting problem implicitly caused by ADA. FADA is tested and evaluated using synthetic dataset, COREL dataset and three different face datasets. The experimental results show FADA is more effective and computationally more efficient than ADA for image classification. {\textcopyright} Springer-Verlag Berlin Heidelberg 2007.",
keywords = "Adaptive discriminant analysis, Image classification",
author = "Yijuan Lu and Jingsheng Ma and Qi Tian",
year = "2007",
language = "English",
isbn = "9783540772545",
volume = "4810 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "1--9",
booktitle = "Advances in Multimedia Information Processing - PCM 2007 - 8th Pacific Rim Conference on Multimedia, Proceedings",
note = "8th Pacific-Rim Conference on Multimedia, PCM 2007 ; Conference date: 11-12-2007 Through 14-12-2007",
}