https://scholars.lib.ntu.edu.tw/handle/123456789/176021
Title: | 參數選擇對水稻品種鑑別的影響 THE EFFECT OF PARAMETER SELECTION ON CLASSIFYING PADDY RICE |
Authors: | 劉昌群 蕭介宗 彭敬益 洪梅珠 沈明來 Liu, Chang-Chun Shaw, Jai-Tsung Poong, Keen-Yik Hong, Mei-Chu Shen Ming-Lai |
Keywords: | 機器視覺;類神經網路;水稻;參數選擇;鑑別;Machine vision;Artificial neural network;Paddy rice;Parameter selection;Classification | Issue Date: | Mar-2005 | Publisher: | 臺北市:國立臺灣大學生物產業機電工程學系 | Abstract: | 17. 農業機械學刊第14 卷第1 期2005 年3 月. 參數選擇對水稻品種鑑別的影響. 劉昌群. 1. ,蕭介宗. 2. ,彭敬益. 3. ,洪梅珠. 4. ,沈明來. 5. 1. 國立台灣大學生物產業 機電工程學系研究生. 2. 國立台灣大學生物產業機電工程學系教授,本文通訊作者 Considering different shape factors and color intensities of five varieties of paddy rice as parameters, four models were established by a back-propagation neural network and were used to study the validation and classification rates affected by choosing different parameters. With 60 parameters, the average validation and classification rates were 92.24% and 92.0% respectively. If the most effective 50 parameters were chosen by loading values in the first principal component, the average validation and classification rates were 91.77 % and 90.0% respectively. 30 parameters selected from the correlation coefficient matrix to build up the model, the average validation and classification rates were 89.18 % and 91.4% respectively. If the most effective 20 parameters were chosen from model training, the average validation and classification rates were 90.59 % and 91.8% respectively, which could be the best model for classifying due to its less parameters and better stability. |
URI: | http://ntur.lib.ntu.edu.tw//handle/246246/20060927122950210444 | Other Identifiers: | 20060927122950210444 |
Appears in Collections: | 生物機電工程學系 |
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14-1-3.pdf | 2.99 MB | Adobe PDF | View/Open |
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