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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fan Wang Guihua Er Qionghai Dai |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Autom., Tsinghua Univ., Beijing (Fan Wang; Guihua Er; Qionghai Dai) |
| Abstract | We propose to improve the effectiveness and scalability of graph based manifold ranking methods in image retrieval applications by emphasizing reliable images while damping the effect of noisy or irregular ones. Label information is firstly passed between most reliable data points, then propagated to less reliable ones on manifold structure. By treating these images inequivalently, undesirable effect of noisy samples is greatly reduced, thus effectiveness of manifold ranking algorithms is enhanced. Also, graph size in terms of number of nodes and edges is dramatically reduced, resulting in a great speed-up of the algorithm. Our experiment on real world image data set demonstrates the effectiveness of the proposed approach. |
| Starting Page | 173 |
| Ending Page | 176 |
| File Size | 148391 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424417650 |
| ISSN | 15224880 |
| DOI | 10.1109/ICIP.2008.4711719 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-10-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image retrieval Content based retrieval Spine Scalability Damping Noise reduction Clustering algorithms Information retrieval Image databases Erbium clustering manifold ranking scalability |
| Content Type | Text |
| Resource Type | Article |
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