Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD
In this work, we present a novel 3D descriptor, Improved Dexel Representation (IDR), which assists to input holistic information from an engineering CAD model to Convolutional Neural Network (CNN) based manufacturing applications. The IDR carries the model's position, size, and surface informat...
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Veröffentlicht in: | IEEE transactions on industrial informatics 2021-12, p.1-1 |
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creator | Fu, Xingyu Peddireddy, Dheeraj Aggarwal, Vaneet Jun, Martin Byung-Guk |
description | In this work, we present a novel 3D descriptor, Improved Dexel Representation (IDR), which assists to input holistic information from an engineering CAD model to Convolutional Neural Network (CNN) based manufacturing applications. The IDR carries the model's position, size, and surface information, which not only provides high resolution to small-scale local (machining) features but also has the potential to reconstruct the original CAD model. Data conversion algorithms between IDR and other CAD models (mesh and NURBS model) are efficient. CNNs with IDR input can largely improve the prediction accuracy compared to other 3D descriptors, which reaches 98.8\% in the modified Machining-Process-Identifier dataset and 100\% on the FeatureNet style 3-class dataset. IDR benefits both the manufacturing industry and other CAD-related deep learning applications in engineering fields. |
doi_str_mv | 10.1109/TII.2021.3136167 |
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IDR benefits both the manufacturing industry and other CAD-related deep learning applications in engineering fields.</description><identifier>ISSN: 1551-3203</identifier><identifier>EISSN: 1941-0050</identifier><identifier>DOI: 10.1109/TII.2021.3136167</identifier><identifier>CODEN: ITIICH</identifier><language>eng</language><publisher>IEEE</publisher><subject>3D descriptor ; Computational modeling ; ComputerAided Design (CAD) ; Convolutional Neural Network (CNN) ; Convolutional neural networks ; feature recognition ; Machining ; Manufacturing ; Neural networks ; Solid modeling ; Three-dimensional displays</subject><ispartof>IEEE transactions on industrial informatics, 2021-12, p.1-1</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9653815$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9653815$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Fu, Xingyu</creatorcontrib><creatorcontrib>Peddireddy, Dheeraj</creatorcontrib><creatorcontrib>Aggarwal, Vaneet</creatorcontrib><creatorcontrib>Jun, Martin Byung-Guk</creatorcontrib><title>Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD</title><title>IEEE transactions on industrial informatics</title><addtitle>TII</addtitle><description>In this work, we present a novel 3D descriptor, Improved Dexel Representation (IDR), which assists to input holistic information from an engineering CAD model to Convolutional Neural Network (CNN) based manufacturing applications. 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IDR benefits both the manufacturing industry and other CAD-related deep learning applications in engineering fields.</description><subject>3D descriptor</subject><subject>Computational modeling</subject><subject>ComputerAided Design (CAD)</subject><subject>Convolutional Neural Network (CNN)</subject><subject>Convolutional neural networks</subject><subject>feature recognition</subject><subject>Machining</subject><subject>Manufacturing</subject><subject>Neural networks</subject><subject>Solid modeling</subject><subject>Three-dimensional displays</subject><issn>1551-3203</issn><issn>1941-0050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9ir2KwkAURgdR0FV7YZt5gcR7c51otpNk1RQKir0MeiMj5oeZUfTtN8XWFh_nwPmEmCCEiJBMj3keRhBhSEgxxvOOGGAywwBAQbd1pTCgCKgvvpy7AdAcKBmIfV42tn7yRWb84rs8cGPZceW1N3X1I5eSMpnudnLNdcnevtufO1vT-NrKot1WV49Cn_3Dmuoq02U2Er1C3x2P_zkU36vfY7oJDDOfGmtKbd-nJFa0QEWf6x8sAT5x</recordid><startdate>20211215</startdate><enddate>20211215</enddate><creator>Fu, Xingyu</creator><creator>Peddireddy, Dheeraj</creator><creator>Aggarwal, Vaneet</creator><creator>Jun, Martin Byung-Guk</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope></search><sort><creationdate>20211215</creationdate><title>Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD</title><author>Fu, Xingyu ; Peddireddy, Dheeraj ; Aggarwal, Vaneet ; Jun, Martin Byung-Guk</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_96538153</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>3D descriptor</topic><topic>Computational modeling</topic><topic>ComputerAided Design (CAD)</topic><topic>Convolutional Neural Network (CNN)</topic><topic>Convolutional neural networks</topic><topic>feature recognition</topic><topic>Machining</topic><topic>Manufacturing</topic><topic>Neural networks</topic><topic>Solid modeling</topic><topic>Three-dimensional displays</topic><toplevel>online_resources</toplevel><creatorcontrib>Fu, Xingyu</creatorcontrib><creatorcontrib>Peddireddy, Dheeraj</creatorcontrib><creatorcontrib>Aggarwal, Vaneet</creatorcontrib><creatorcontrib>Jun, Martin Byung-Guk</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><jtitle>IEEE transactions on industrial informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Fu, Xingyu</au><au>Peddireddy, Dheeraj</au><au>Aggarwal, Vaneet</au><au>Jun, Martin Byung-Guk</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD</atitle><jtitle>IEEE transactions on industrial informatics</jtitle><stitle>TII</stitle><date>2021-12-15</date><risdate>2021</risdate><spage>1</spage><epage>1</epage><pages>1-1</pages><issn>1551-3203</issn><eissn>1941-0050</eissn><coden>ITIICH</coden><abstract>In this work, we present a novel 3D descriptor, Improved Dexel Representation (IDR), which assists to input holistic information from an engineering CAD model to Convolutional Neural Network (CNN) based manufacturing applications. 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subjects | 3D descriptor Computational modeling ComputerAided Design (CAD) Convolutional Neural Network (CNN) Convolutional neural networks feature recognition Machining Manufacturing Neural networks Solid modeling Three-dimensional displays |
title | Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD |
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