Name
Title | ||
|---|---|---|
An Extension Of The Student'S T-Distribution Mixture Model And The Gradient Descent Method |
Abstract | ||
|---|---|---|
A new Student's t-distribution finite mixture model is proposed which incorporates the local spatial information of the pixels. The pixels' label probability proportions are explicitly modelled as probability vectors in the proposed model. We use the gradient descend method to estimate the parameters of the proposed model. Comprehensive experiments are performed for synthetic and natural grayscale images. The experimental results demonstrate that the superiority of the proposed model over some other models. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.4304/jcp.8.7.1750-1757 | JOURNAL OF COMPUTERS |
Keywords | Field | DocType |
Spatially variant finite mixture model, Student's, t-distribution, Image segmentation, Gradient descent | Spatial analysis,Gradient method,Gradient descent,Pattern recognition,Computer science,Student's t-distribution,Image segmentation,Pixel,Artificial intelligence,Mixture model,Machine learning,Grayscale | Journal |
Volume | Issue | ISSN |
8 | 7 | 1796-203X |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taisong Xiong | 1 | 43 | 4.42 |
| Jianping Gou | 2 | 48 | 3.47 |
| Yunbo Rao | 3 | 54 | 12.25 |