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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wongsriworaphon, A. Pathumnakul, S. Arnonkijpanich, B. |
| Copyright Year | 2012 |
| Description | Author affiliation: Dept. of Math., Khon Kaen Univ., Khon Kaen, Thailand (Arnonkijpanich, B.) || Dept. of Ind. Eng., Khon Kaen Univ., Khon Kaen, Thailand (Wongsriworaphon, A.; Pathumnakul, S.) |
| Abstract | Stockman or farmers always have difficulty recognition of pig mass in their farms. The typical approach is to approximate from age of pigs, daily-given feed, or from experience of human vision. Another practical approach to instantly measure mass of pigs is to use machine vision. The objective of this paper is to use a developed machine vision to analyze pig mass for detection of size and weight of pigs in farm. The pig mass is processed from physical features captured from digital image and their liveweights are approximated from artificial neural network. This neural network model is based on vector-quantized temporal associative memory (VQTAM) and locally linear embedding (LLE). The elementary results showed that the mass approximation of pig weight had acceptable accuracy and it was practical in pig farms. |
| Sponsorship | IEEE Singapore Sect. |
| Starting Page | 856 |
| Ending Page | 860 |
| File Size | 1613691 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467329453 |
| ISSN | 2157362X |
| DOI | 10.1109/IEEM.2012.6837861 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-12-10 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | locally linear embedding Machine vision Digital images VQTAM Neurons Artificial neural networks Educational institutions Vectors Approximation methods Pig weighing system |
| Content Type | Text |
| Resource Type | Article |
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