title: Application of a multi-structure neural network (MSNN) to sorting pistachio nuts.
abstract: A multi-structure neural network (MSNN) classifier consisting of four discriminators followed by a maximum selector was designed and applied to classification of four grades of pistachio nuts. Each discriminator was a multi-layer feed-forward neural network with two hidden layers and a single-neuron output layer. Fourier descriptors of the nuts' boundaries and their area were used as the recognition features. The individual discriminators were trained using a biased technique and a back-propagation algorithm. The MSNN classifier gave an average classification performance of 95.0%. This was an increase of 14.8% over the performance of a multi-layer neural network (MLNN) with similar complexity for classifying the same set of patterns.
authors.affiliation: Department of Ag. & Bio. Engineering, University of Saskatchewan, Canada.
authors.forename: A
authors.initials: A
authors.lastname: Ghazanfari
authors.forename: A
authors.initials: A
authors.lastname: Kusalik
authors.forename: J
authors.initials: J
authors.lastname: Irudayaraj
mesh_terms: D004193:Discrimination Learning; D016571:Neural Networks, Computer; D009754:Nuts / Q000145:classification*; D011786:Quality Control; D015203:Reproducibility of Results