Title :
An ensemble classifier based on a bionic model and SVM for machine olfaction
Author_Institution :
Coll. of Comput. Sci. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou, China
Abstract :
This paper presents a novel approach for pattern recognition in machine olfaction by constructing an ensemble classifier using a bionic olfactory neural network, namely KIII model, and support vector machine (SVM). In this approach, feature vectors are firstly processed by KIII model which stimulates information processing function of olfactory bulb, and then classified by SVM. In the experiment to classify aroma of reconstituted milk from that of fresh milk, this approach shows promising accuracy for complex data and is more robust than pure SVM.
Keywords :
chemioception; dairy products; neural nets; pattern classification; production engineering computing; support vector machines; bionic model; bionic olfactory neural network; ensemble classifier; fresh milk; machine olfaction; milk classification; olfactory bulb; pattern recognition; reconstituted milk; support vector machines; Biological system modeling; Classification algorithms; Dairy products; Data models; Olfactory; Support vector machines; Training; SVM; ensemble classifier; machine olfaction; olfactory model; pattern recognition;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5647615