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    National Tsing Hua University Institutional Repository > 工學院  > 工業工程與工程管理學系 > 期刊論文 >  ANN-based 3D part search with different levels of detail (LOD) in negative feature decomposition

    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/27059

    Title: ANN-based 3D part search with different levels of detail (LOD) in negative feature decomposition
    Authors: Chih-Hsing Chu;Han-Chung Cheng;Eric Wang;Yong-Se Kim
    教師: 瞿志行
    Date: 2009
    Publisher: Elsevier
    Relation: Expert Systems with Applications, Volume 36, Issue 8, October 2009, Pages 10905-10913
    Keywords: Similarity assessment
    Levels of detail (LOD)
    Negative feature
    Feature recognition
    Part search
    Design retrieval
    Abstract: © 2009 Elsevier - Duplicate designs consume a large amount of enterprise resources during product development. Automatic search for similar parts is an effective solution for design reuse. Previous studies have only concerned similarity assessment based on complete 3D models, which may produce unsatisfactory result in practice. This paper proposes a novel scheme which incorporates the concept of LOD (levels of detail) into 3D part search. The scheme allows searching with different LOD variants created from the negative feature tree (NFT) of a solid model. A back-propagation artificial neural network is established to combine the D2-based similarity evaluation at each level of NFT. A human cognition model (HCM) is obtained by training the network with a set of data generated from a human experiment of similarity ranking. Search examples based on HCM show that the proposed scheme provides a practical tool for retrieval of similar part models.
    URI: http://www.elsevier.com/
    Appears in Collections:[工業工程與工程管理學系] 期刊論文

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