PCA-based branch and bound search algorithms for computing K nearest neighbors-Reference-Cited by-同舟云学术

PCA-based branch and bound search algorithms for computing K nearest neighbors

Published:2003-06 Issue:9-10 Volume:24 Page:1437-1451
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

D’haes Wim,van Dyck Dirk,Rodet Xavier

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference16 articles.

1. An efficient branch and bound search algorithm for computing k nearest neighbors in a multidimensional vector space;D’haes;IEEE Advanced Concepts Intelligent Vision Systems (ACIVS),2002

2. Fast nearest neighbor search in dissimilarity spaces;Faragó;IEEE Trans. Pattern Anal. Mach. Intell.,1993

3. Statistical Pattern Recognition;Fukunaga,1990

4. A branch and bound algorithm for computing k nearest neighbors;Fukunaga;IEEE Trans. Comput.,1975

5. Juan, A., Vidal, E., Aibar, P., 1998. Fast k nearest neighbor searching through extended versions of the approximating and eliminating search algorithm (AESA). In: Proceedings of the 14th ICPR, vol. I, pp. 828–830

Cited by 7 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. A new extracting algorithm of k nearest neighbors searching for point clouds;Pattern Recognition Letters;2014-11

2. Electro/Acoustic Improvisation and Deeply Listening Machines;Journal of New Music Research;2013-12

3. Fast k most similar neighbor classifier for mixed data (tree k-MSN);Pattern Recognition;2010-03

4. A practical approach to the 2D incremental nearest-point problem suitable for different point distributions;Pattern Recognition;2008-02

5. Corpus-Based Concatenative Synthesis;IEEE Signal Processing Magazine;2007-03