An artificial neural network (back propagation neural network) based on morphological and fractal leaf and flower parameters was developed for the characterization of three Banksia integrifolia subspecies and the identification of nine unnamed morphotypes. Results indicated that the network can be effectively and successfully used to discriminate among morphotypes using simple dedicated instruments, such as a PC and an optical scanner. The new method also as a complementary approach to botanical identification, being capable of separating all the tested Banksia integrifolia accessions and of creating associations between the known subspecies and the unnamed accessions.

Discrimination and identification of morphotypes of Banksia integrifolia (Proteaceae) by an Artificial Neural Network (ANN), based on morphological and fractal parameters of leaves and flowers / C.Pandolfi; G.Messina; S.Mugnai; E.Azzarello; E.Masi; K.Dixon; S.Mancuso. - In: TAXON. - ISSN 0040-0262. - STAMPA. - 58:(2009), pp. 925-933.

Discrimination and identification of morphotypes of Banksia integrifolia (Proteaceae) by an Artificial Neural Network (ANN), based on morphological and fractal parameters of leaves and flowers

PANDOLFI, CAMILLA;MESSINA, GIUSEPPE;MUGNAI, SERGIO;AZZARELLO, ELISA;MASI, ELISA;MANCUSO, STEFANO
2009

Abstract

An artificial neural network (back propagation neural network) based on morphological and fractal leaf and flower parameters was developed for the characterization of three Banksia integrifolia subspecies and the identification of nine unnamed morphotypes. Results indicated that the network can be effectively and successfully used to discriminate among morphotypes using simple dedicated instruments, such as a PC and an optical scanner. The new method also as a complementary approach to botanical identification, being capable of separating all the tested Banksia integrifolia accessions and of creating associations between the known subspecies and the unnamed accessions.
2009
58
925
933
C.Pandolfi; G.Messina; S.Mugnai; E.Azzarello; E.Masi; K.Dixon; S.Mancuso
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/318592
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