6 January 1995 Comparison of classification techniques for the identification of Australian wheat varieties
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Proceedings Volume 2345, Optics in Agriculture, Forestry, and Biological Processing; (1995) https://doi.org/10.1117/12.198864
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States
Abstract
Pattern recognition techniques have some attraction for the automatic identification of seeds as they are fast, non-destructive and easily applied. In this paper, the performance of quadratic discriminant functions and one form of artificial neural network are compared for the task of identifying Australian wheat varieties. This is a complex problem as the kernels are very similar in appearance, and factors other than variety significantly influence shape. It is shown both approaches have some similarity in performance, but discriminant functions provide a superior result and are more easily applied. There is, though, some opportunity for further refinement of the artificial neural network.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Douglas Graham Myers, Timo A. Vuori, "Comparison of classification techniques for the identification of Australian wheat varieties", Proc. SPIE 2345, Optics in Agriculture, Forestry, and Biological Processing, (6 January 1995); doi: 10.1117/12.198864; https://doi.org/10.1117/12.198864
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