NDLI: The fresh classification of pork detection based on multi-data fusion

Content Provider	IEEE Xplore Digital Library
Author	Guo Peiyuan Bi Song Chen Tianhua Xu Guannan Liu Xing
Copyright Year	2010
Description	Author affiliation: College of Computer and Information Engineering Beijing Technology and Business University, 100037, China (Guo Peiyuan; Bi Song; Chen Tianhua; Xu Guannan; Liu Xing)
Abstract	In order to find a quick valid scientific way to identify meat freshness, the article analyses the measuring mechanism of identifying to fresh degree of meat, and designs one set of intellectual detection and identification system that is based on electronic information technology, photoelectric detection technique, image processing technology and neural network model recognition technology. In order to achieve the freshness of the pork inspection classification identification, neural network technology micro-parameters of non-coherent multi-data fusion detection methods was Researched.
Starting Page	2735
Ending Page	2738
File Size	140431
Page Count	4
File Format	PDF
ISBN	9781424462636
e-ISBN	9787894631046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Association of Aut
Subject Keyword	Proteins Pattern-Recognition Microorganisms Neural Network Image color analysis Identifying Meat Freshness Artificial neural networks Transforms Software Plaque Area Photo-electricity Measuring Standards
Content Type	Text
Resource Type	Article

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The fresh classification of pork detection based on multi-data fusion