Kernel Principal Component Analysis for Content Based Image Retrieval-Reference-Cited by-同舟云学术

Kernel Principal Component Analysis for Content Based Image Retrieval

Published:2005 Issue: Volume: Page:844-849
ISSN:0302-9743
Container-title:Advances in Knowledge Discovery and Data Mining
language:
Short-container-title:

Author:

Cha Guang-Ho

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11430919_100.pdf

Reference14 articles.

1. Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*-tree: An efficient and robust access method for points and rectangles. In: Proc. of ACM SIGMOD Conf., pp. 322–331 (1990)

2. Cha, G.-H., Chung, C.-W.: A New Indexing Scheme for Content-Based Image Retrieval. Multimedia Tools and Applications 6, 263–288 (1998)

3. Cha, G.-H., Zhu, X., Petkovic, D., Chung, C.-W.: An Efficient Indexing Method for Nearest Neighbor Searches in High-Dimensional Image Databases. IEEE Trans. on Multimedia, 76–87 (2002)

4. Chakrabarti, K., Mehrotra, S.: Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces. In: Proc. of the Int’l Conf. on VLDB, pp. 89–100 (2000)

5. Diamantaras, K.I., Kung, S.Y.: Principal Component Neural Networks. Wiley, New York (1996)

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-level diversification approach of semantic-based image retrieval results;Progress in Artificial Intelligence;2019-06-22

2. RKF-PCA: Robust kernel fuzzy PCA;Neural Networks;2009-07

3. Content Based Image Retrieval Based on a Nonlinear Similarity Model;Computational Science and Its Applications - ICCSA 2006;2006