Automatic Classification of 3D Drosophila Calyx Images

ASIA unversity > 資訊學院 > 會議論文 > Item 310904400/7124

請使用永久網址來引用或連結此文件: http://asiair.asia.edu.tw/ir/handle/310904400/7124

題名:	Automatic Classification of 3D Drosophila Calyx Images
作者:	Pei-Ling Liu;Henry Horng-Shing Lu;Ann-Shyn Chiang
貢獻者:	Institute of Information Science, Academia Sinica.；Institute of Statistics,National Chiao-Tung University. (Taiwan)；Institute of Biotechnology, National Tsing-Hua University. (Taiwan)
關鍵詞:	Feature Extraction;SVM
日期:	2007-12-20
上傳時間:	2010-01-12 08:23:21 (UTC+0)
出版者:	亞洲大學資訊學院;中華電腦學會
摘要:	In this research, the main purpose is the application of an automatic classification method for six kinds of 3D Drosophila Calyx Images. We have six different kinds of image data. We will use extracted features describing the spatial dispersion and connectivity of 3D olfactory neuron pathway for classification. It is worth noting that much of the image data contain redundant information so we determine the essentialness of these features by cross validation accuracy. In the leave-one-out cross validation analysis, a six-category SVM classifier is three times better than random guess. Besides, there is no evidence of over-fitting, because compared to 3D spatial RST-invariant feature set alone, the 64-view Rotational Skeleton Endpoint feature set together with it raises the accuracy rate.
關聯:	2007NCS全國計算機會議 12-20~21
顯示於類別:	[資訊學院] 會議論文

文件中的檔案:

檔案	大小	格式	瀏覽次數
7033.pdf	511Kb	Adobe PDF	683	檢視/開啟

在ASIAIR中所有的資料項目都受到原著作權保護.