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KES
2007
Springer

Automated Ham Quality Classification Using Ensemble Unsupervised Mapping Models

13 years 9 months ago
Automated Ham Quality Classification Using Ensemble Unsupervised Mapping Models
This multidisciplinary study focuses on the application and comparison of several topology preserving mapping models upgraded with some classifier ensemble and boosting techniques in order to improve those visualization capabilities. The aim is to test their suitability for classification purposes in the field of food industry and more in particular in the case of dry cured ham. The data is obtained from an electronic device able to emulate a sensory olfative taste of ham samples. Then the data is classified using the previously mentioned techniques in order to detect which batches have an anomalous smelt (acidity, rancidity and different type of taints) in an automated way.
Bruno Baruque, Emilio Corchado, Hujun Yin, Jordi R
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where KES
Authors Bruno Baruque, Emilio Corchado, Hujun Yin, Jordi Rovira, Javier González
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