INTELLIGENT CLASSIFIERS FOR NON-DESTRUCTIVE DETERMINATION OF FOOD QUALITY

Tania P. Titova, Veselin G. Nachev, Chavdarv I. Damyanov, Plamen I. Nikovski

DOI Number
-
First page
19
Last page
30

Abstract


The paper analyzes the possibilities to non-destructively determine food quality (potatoes, eggs) by means of the spectra of transmission in the visible and near-infrared regions of the electromagnetic spectrum. The research includes the creation and testing of a training sample of representative samples and the evaluation of the possibilities for classification using Neural Classifier and Support Vector Machines method (SVM).


Key words: non-destructive quality evaluation, pattern recognition, food quality, classifiers


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References


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