完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Arwatchananukul, Sujitra | en_US |
dc.contributor.author | Charoenkwan, Phasit | en_US |
dc.contributor.author | Xu, Dan | en_US |
dc.date.accessioned | 2017-04-21T06:49:18Z | - |
dc.date.available | 2017-04-21T06:49:18Z | - |
dc.date.issued | 2015 | en_US |
dc.identifier.isbn | 978-1-4673-7290-9 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/135954 | - |
dc.description.abstract | Paphiopedilum Orchid Flowers (POF) are colorful wildflowers and also endangered plants since they bloom only one time per year. There are many species with a similar appearance, which makes it difficult and laborious to classify. Thus, we propose a novel Paphiopedilum Orchid Classifier (POC) based on Neural Network, utilizing the Color and Segmentation-based Fractal Texture Analysis (SFTA) features. In the classification of 11 POF species, POC achieved 97.64% of 10-fold cross validation accuracy. Besides, we also propose a new POF dataset consisting of 100 samples for each species and illustrated the prediction performance of several renowned classifiers such as Naive Bayes, K-nearest and Decision Tree. According to research result, we hope that POC can assists botanists to classify POF for further breed selection and adaptation. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Paphiopedilum Orchid Flower | en_US |
dc.subject | Color moments | en_US |
dc.subject | Histogram | en_US |
dc.subject | SFTA | en_US |
dc.subject | Neural Network | en_US |
dc.title | POC: Paphiopedilum Orchid Classifier | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | PROCEEDINGS OF 2015 IEEE 14TH INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS & COGNITIVE COMPUTING (ICCI*CC) | en_US |
dc.citation.spage | 206 | en_US |
dc.citation.epage | 212 | en_US |
dc.contributor.department | 生物資訊及系統生物研究所 | zh_TW |
dc.contributor.department | Institude of Bioinformatics and Systems Biology | en_US |
dc.identifier.wosnumber | WOS:000380466100033 | en_US |
dc.citation.woscount | 0 | en_US |
顯示於類別: | 會議論文 |