Please use this identifier to cite or link to this item:
http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6613Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Marroquin, Jose L. | - |
| dc.creator | Girosi, Federico | - |
| dc.date | 2004-10-08T20:34:28Z | - |
| dc.date | 2004-10-08T20:34:28Z | - |
| dc.date | 1993-01-01 | - |
| dc.date.accessioned | 2013-10-09T02:46:09Z | - |
| dc.date.available | 2013-10-09T02:46:09Z | - |
| dc.date.issued | 2013-10-09 | - |
| dc.identifier | AIM-1390 | - |
| dc.identifier | http://hdl.handle.net/1721.1/6613 | - |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/1721 | - |
| dc.description | In this paper we present some extensions to the k-means algorithm for vector quantization that permit its efficient use in image segmentation and pattern classification tasks. It is shown that by introducing state variables that correspond to certain statistics of the dynamic behavior of the algorithm, it is possible to find the representative centers fo the lower dimensional maniforlds that define the boundaries between classes, for clouds of multi-dimensional, mult-class data; this permits one, for example, to find class boundaries directly from sparse data (e.g., in image segmentation tasks) or to efficiently place centers for pattern classification (e.g., with local Gaussian classifiers). The same state variables can be used to define algorithms for determining adaptively the optimal number of centers for clouds of data with space-varying density. Some examples of the applicatin of these extensions are also given. | - |
| dc.format | 95179 bytes | - |
| dc.format | 1158231 bytes | - |
| dc.format | application/octet-stream | - |
| dc.format | application/pdf | - |
| dc.language | en_US | - |
| dc.relation | AIM-1390 | - |
| dc.title | Some Extensions of the K-Means Algorithm for Image Segmentation and Pattern Classification | - |
| Appears in Collections: | MIT Items | |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.