Abstract
In order to automize on-line selection of biological products, it is necessary to determine relationships between human sensory evaluation (like the beauty of flowerplants), and physical measurements on objects (like machine vision images). Classical methods of image processing and statistics, are combined with neural network techniques. The research deals with methods for the selection of significant parameters for the judgement, and methods for decision learning and generation: for both types of methods, classical statistics and neural network technics are either compared or combined. Interest of the various combinations are discussed, through the application on beauty selection of flowerplants.
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© 1993 Springer-Verlag Berlin Heidelberg
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Ros, F., Brons, A., Sevila, F., Rabatel, G., Touzet, C. (1993). Combination of neural network and statistical methods for sensory evalution of biological products: On-line beauty selection of flowers. In: Mira, J., Cabestany, J., Prieto, A. (eds) New Trends in Neural Computation. IWANN 1993. Lecture Notes in Computer Science, vol 686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56798-4_228
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DOI: https://doi.org/10.1007/3-540-56798-4_228
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