DocumentCode
2085804
Title
Application of support vector machines in detection technology based on near infrared spectroscopy
Author
Wu Jingzhu ; Liu Cuiling ; Sun Xiaorong
Author_Institution
Sch. of Comput. Sci. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
fYear
2010
fDate
29-31 July 2010
Firstpage
2796
Lastpage
2798
Abstract
This paper discusses the application of support vector machines in detection technology based on near infrared spectroscopy. Results of qualitative test indicate that the combination of SVM and NIR can be used as a fast, convenient, nondestructive and safe technology to identify standard and sub-standard milk powder. Results of quantitative test indicate SVM has better performance than BP neural network in building quantitative model based on NIR.
Keywords
backpropagation; dairy products; image recognition; infrared spectroscopy; optical images; support vector machines; backpropagation neural network; detection technology; near infrared spectroscopy; sub-standard milk powder; support vector machines; Artificial neural networks; Business; Electronic mail; Mathematical model; Pattern recognition; Spectroscopy; Support vector machines; BP Neural Network; Near Infrared Spectroscopy; Pattern Recognition; Support Vector Machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2010 29th Chinese
Conference_Location
Beijing
Print_ISBN
978-1-4244-6263-6
Type
conf
Filename
5572599
Link To Document