Classifying the patterns of moving point lights attached on actor's bodies with self-organizing map often fails to get successful results with its original unsupervised learning algorithm. This paper exploits a structure-adaptive self-organizing map (SASOM) which adaptively updates the weights, structure and size of the map, resulting in remarkable improvement of pattern classification performance. We have compared the results with those of conventional pattern classifiers and human subjects. SASOM turns out to be the best classifier producing 97.1% of recognition rate on the 312 test data from 26 subjects.
|Title of host publication||ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing|
|Subtitle of host publication||Computational Intelligence for the E-Age|
|Editors||Lipo Wang, Jagath C. Rajapakse, Kunihiko Fukushima, Soo-Young Lee, Xin Yao|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|ISBN (Electronic)||9810475241, 9789810475246|
|Publication status||Published - 2002|
|Event||9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore|
Duration: 2002 Nov 18 → 2002 Nov 22
|Name||ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age|
|Other||9th International Conference on Neural Information Processing, ICONIP 2002|
|Period||02/11/18 → 02/11/22|
Bibliographical noteFunding Information:
This paper was supported by Brain Science and Engineering Research Program sponsored by Korean Ministry of Science and Technology.
© 2002 Nanyang Technological University.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Information Systems
- Signal Processing