Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chang, JY | en_US |
dc.contributor.author | Cho, CW | en_US |
dc.date.accessioned | 2014-12-08T15:25:16Z | - |
dc.date.available | 2014-12-08T15:25:16Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.isbn | 0-7803-9048-2 | en_US |
dc.identifier.issn | 1098-7576 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/17638 | - |
dc.description.abstract | In this paper, we utilize a neural network based machine learning algorithm to segment natural objects in outdoor scene images. We have developed a genetic algorithm based fuzzy ID3 method, which can build a fuzzy decision tree to summarize the regularities existing in the data set. Using this method, we then propose a road scene analysis system, by which natural element segmentation rules can be learned from several road scene images. In the image analysis phase, the natural element regions are obtained through inference on these learned rules. Moreover, we can apply image groundtruthing to further improve the classification accuracy. The testing results have demonstrated that the object segmentation accuracy is quite high. | en_US |
dc.language.iso | en_US | en_US |
dc.title | A new scene analysis using genetic algorithm based fuzzy ID3 method | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | Proceedings of the International Joint Conference on Neural Networks (IJCNN), Vols 1-5 | en_US |
dc.citation.spage | 1770 | en_US |
dc.citation.epage | 1775 | en_US |
dc.contributor.department | 電控工程研究所 | zh_TW |
dc.contributor.department | Institute of Electrical and Control Engineering | en_US |
dc.identifier.wosnumber | WOS:000235178002081 | - |
Appears in Collections: | Conferences Paper |