Neural network models for product image design

Yang Cheng Lin, Hsin Hsi Lai, Chung Hsing Yeh

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)

Abstract

This paper develops four neural network models to help product developers work out a combination of product form elements for best matching a given product image. By applying four most widely used rules for determining the number of hidden neurons, these four models can be used to determine the value of the product image for a given combination of product form elements. An experimental study on mobile phones is conducted to evaluate the performance of these four models. The result of this study shows that there is no best rule for building the models and the performance of these models does not differ significantly. Although the mobile phones are chosen as the object of the experimental study, the approach presented is applicable to other products where a combination of form or other design elements is to be determined for matching a desirable product image.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Pages618-624
Number of pages7
ISBN (Print)9783540232056
Publication statusPublished - 2004
EventInternational Conference on Knowledge-Based and Intelligent Information and Engineering Systems 2004 - Wellington, New Zealand
Duration: 20 Sep 200425 Sep 2004
Conference number: 8th

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3215
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Knowledge-Based and Intelligent Information and Engineering Systems 2004
Abbreviated titleKES 2004
CountryNew Zealand
CityWellington
Period20/09/0425/09/04

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