Name
Abstract | ||
|---|---|---|
Learning and neighborhood algorithm are an important part of 3D SOM algorithm. The five kinds of learning algorithm and Three kinds of neighborhood shape and three kinds of neighborhood decay functions for three-dimensional self-organizing feature maps (3D SOM) algorithm were proposed in this paper. And the algorithm were applied in three-dimensional image compression coding. Experimental results show that the quadratic function learning algorithm achieved the best peak signal to noise ratio (PSNR) and the 3D orthogonal cross neighborhood shape and memory function algorithm has better peak signal to noise ratio (PSNR) and subject quality. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICSAI.2018.8599510 | 2018 5TH INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI) |
Keywords | Field | DocType |
self-organizing maps, three-dimensional image coding, pattern recognition, learning algorithm, neighborhood algorithm | Peak signal-to-noise ratio,Computer science,Algorithm,Coding (social sciences),Self-organizing map,Quadratic function,Image compression | Conference |
ISSN | Citations | PageRank |
2474-0217 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xueyan Zhang | 1 | 0 | 0.34 |
| Hongsong Li | 2 | 302 | 19.13 |
| Fulin Cheng | 3 | 0 | 0.34 |
| Yanhua Wang | 4 | 47 | 6.35 |
| Xinyu Ai | 5 | 0 | 0.34 |