| dc.contributor | 應數系 | en_US |
| dc.creator (作者) | 曾正男 | zh_TW |
| dc.creator (作者) | Tzeng, Jeng-Nan | en_US |
| dc.date (日期) | 2012.03 | en_US |
| dc.date.accessioned | 22-May-2014 11:15:03 (UTC+8) | - |
| dc.date.available | 22-May-2014 11:15:03 (UTC+8) | - |
| dc.date.issued (上傳時間) | 22-May-2014 11:15:03 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/66142 | - |
| dc.description.abstract (摘要) | In the image recognition field, there are many proposed artificial intelligence techniques for finding features that can differentiate data belonging to different classes. Features or components which appear ambiguous for separating data belonging to different classes are usually left out in this field. In this paper, we will demonstrate that by proper design those ambiguous components can still be used for differentiating data. We proposed an association rules based method for designing an image classifier that can distinguish natural images and text images. Our experiments indicate that when existing approaches fail to carry out correct classification, our method can undoubtedly achieve better resu | en_US |
| dc.format.extent | 881842 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.relation (關聯) | The International Journal of Intelligent Technologies and Applied Statistics (IJITAS), 5(1), 101-108 | en_US |
| dc.subject (關鍵詞) | Association rules ; Image recognition and ambiguous region | en_US |
| dc.title (題名) | Classification in image recognition by ambiguous components | en_US |
| dc.type (資料類型) | article | en |
