Name
Title | ||
|---|---|---|
Re-weighting relevance feedback image retrieval algorithm based on particle swarm optimization |
Abstract | ||
|---|---|---|
Aiming at the inflexible re-weighting problem of relevance feedback (RF) in image retrieval, a re-weighting relevance feedback method utilizing particle swarm optimization (PSORW-RF) is proposed. Firstly, initialize feature weightings randomly, then use the variances of the positive and negative feedback samples' features as study principle, utilize particle swarm optimization (PSO) algorithm to optimize weightings according to user's retrieval requirement, and obtain retrieval results at last. Experiments show that the proposed algorithm is validity. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICNC.2010.5584092 | ICNC |
Keywords | Field | DocType |
reweighting relevance feedback method,negative feedback,re-weighting,particle swarm optimisation,image retrieval,relevance feedback,positive feedback,user retrieval requirement,particle swarm optimization,optimization,radio frequency | Particle swarm optimization,Distance measurement,Weighting,Relevance feedback,Computer science,Negative feedback,Image retrieval,Algorithm,Positive feedback,Multi-swarm optimization,Artificial intelligence,Machine learning | Conference |
Volume | ISBN | Citations |
7 | 978-1-4244-5958-2 | 1 |
PageRank | References | Authors |
0.49 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangli Xu | 1 | 3 | 1.91 |
| Xiangdong Liu | 2 | 2 | 0.84 |
| Zhezhou Yu | 3 | 22 | 5.50 |
| Chunguang Zhou | 4 | 543 | 52.37 |
| Libiao Zhang | 5 | 34 | 7.03 |