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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pican, N. Trucco, E. Ross, M. Lane, D.M. Petillot, Y. Tena Ruiz, I. |
| Copyright Year | 1998 |
| Description | Author affiliation: Lab. of Ocean Syst., Heriot-Watt Univ., Edinburgh, UK (Pican, N.) |
| Abstract | Considers two well-known pattern recognition techniques using texture analysis. The first is the co-occurrence matrix method which relies on statistics and the second is the Kohonen map which comes from the artificial neural networks domain. Both methods are used as feature extraction methods. The extracted feature vectors are fed to a second Kohonen map used as classifier. The authors report briefly some results of their experimental assessment of the merit of each technique when applied to the problem of classifying the seabed from sequences of real images. |
| Starting Page | 424 |
| Ending Page | 428 |
| File Size | 734387 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780350456 |
| DOI | 10.1109/OCEANS.1998.725781 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1998-09-28 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Self organizing feature maps Statistics Feature extraction Data mining Artificial neural networks Image texture analysis Oceans Laboratories Pattern recognition Pattern analysis |
| Content Type | Text |
| Resource Type | Article |
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