In this paper we present a new approach for quality diagnosis of products whereas a neural network represents the main tool. Since flaws can be detected from the level of similarity between datasets, we describe how to compare two data partitions with a quite similar structure as frequently occurs in defect detection. The comparison is obtained by means of an unsupervised neural network algorithm and by the association of an undirected complete weighted graph structure. Then, a graph matching operation returns an estimation of the level of similarity between the datasets.

Multilevel Neural Network approach for general purpose quality diagnosis / Chiarantoni, Ernesto; Girimonte, Daniela; Guaragnella, Cataldo; Vergura, Silvano. - In: ATTI DELLA FONDAZIONE GIORGIO RONCHI. - ISSN 0391-2051. - STAMPA. - LIX, 1-2(2004), pp. 135-138.

Multilevel Neural Network approach for general purpose quality diagnosis

CHIARANTONI, Ernesto;Guaragnella Cataldo;Vergura Silvano
2004-01-01

Abstract

In this paper we present a new approach for quality diagnosis of products whereas a neural network represents the main tool. Since flaws can be detected from the level of similarity between datasets, we describe how to compare two data partitions with a quite similar structure as frequently occurs in defect detection. The comparison is obtained by means of an unsupervised neural network algorithm and by the association of an undirected complete weighted graph structure. Then, a graph matching operation returns an estimation of the level of similarity between the datasets.
2004
Multilevel Neural Network approach for general purpose quality diagnosis / Chiarantoni, Ernesto; Girimonte, Daniela; Guaragnella, Cataldo; Vergura, Silvano. - In: ATTI DELLA FONDAZIONE GIORGIO RONCHI. - ISSN 0391-2051. - STAMPA. - LIX, 1-2(2004), pp. 135-138.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/305
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