计算机科学
人工智能
模式识别(心理学)
统计分类
计算机视觉
作者
Md. Mizanur Rahman,Chalie Charoenlarpnopparut,Prapun Suksompong
标识
DOI:10.1109/eict.2015.7391920
摘要
Electronic noses (E-Nose) are seen to be good substitute to human or animal nose for food, and fruit quality identification. It is also used for explosive and chemical identification. We have generated typical E-Nose data to compare the existing algorithms in terms of training, and testing/validation. We have observed that k-nearest neighbor (k-NN) algorithm, support vector machine (SVM) machine learning algorithms; and radial basis function (RBF), and generalized regression neural networks (GRNNs) shows good odor detection performance. In terms of speed GRNN tops compared to other methods.
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