Neural network based fabric classification and blend composition analysis
Fabric classification plays an important role in the textile industry. Fabrics classification and determining the blend composition involves tedious work and time consumption. Knowledge based systems like artificial neural networks may be successfully employed to over come such problems. In this pap...
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| creator | Desai, J.V. Bandyopadhyay, B. Kane, C.D. |
| description | Fabric classification plays an important role in the textile industry. Fabrics classification and determining the blend composition involves tedious work and time consumption. Knowledge based systems like artificial neural networks may be successfully employed to over come such problems. In this paper, a method is presented to classify and determine blend composition using neural networks. By inputting the mechanical properties measured from Kawabata evaluation system to the neural network, one can get the desired results. A comparative study in the results is made between the backpropagation and radial basis function algorithms to test the suitability of the same for the proposed textile application. |
| doi_str_mv | 10.1109/ICIT.2000.854137 |
| format | Conference Proceeding |
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Fabrics classification and determining the blend composition involves tedious work and time consumption. Knowledge based systems like artificial neural networks may be successfully employed to over come such problems. In this paper, a method is presented to classify and determine blend composition using neural networks. By inputting the mechanical properties measured from Kawabata evaluation system to the neural network, one can get the desired results. A comparative study in the results is made between the backpropagation and radial basis function algorithms to test the suitability of the same for the proposed textile application.</description><identifier>ISBN: 9780780358126</identifier><identifier>ISBN: 0780358120</identifier><identifier>DOI: 10.1109/ICIT.2000.854137</identifier><language>eng</language><publisher>IEEE</publisher><subject>Artificial neural networks ; Fabrics ; Knowledge based systems ; Mechanical factors ; Neural networks ; Neurons ; Pattern recognition ; Radial basis function networks ; Textile industry ; Textile technology</subject><ispartof>Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. 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A comparative study in the results is made between the backpropagation and radial basis function algorithms to test the suitability of the same for the proposed textile application.</description><subject>Artificial neural networks</subject><subject>Fabrics</subject><subject>Knowledge based systems</subject><subject>Mechanical factors</subject><subject>Neural networks</subject><subject>Neurons</subject><subject>Pattern recognition</subject><subject>Radial basis function networks</subject><subject>Textile industry</subject><subject>Textile technology</subject><isbn>9780780358126</isbn><isbn>0780358120</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2000</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj8tqwzAURAWl0JJ6X7rSD9i9V5JtaVlMH4aQbtJ1uHqBWscOlkvJ39eQwDADZ2BgGHtEqBDBPPddv68EAFS6VijbG1aYVsMqWWsUzR0rcv5ee1C1Wuk963fhd6aBj2H5m-YfbikHzyPZOTnuBso5xeRoSdPIafTcDmF1Nx1PU05XSsM5p_zAbiMNORTX3LCvt9d991FuP9_77mVbJgS1lB6N0diCtTFSlNEEL3SrGqyNMUJpaaPUDn3UHpoGBXhjlavBUmOV8kFu2NNlN4UQDqc5HWk-Hy5_5T9ukEvT</recordid><startdate>2000</startdate><enddate>2000</enddate><creator>Desai, J.V.</creator><creator>Bandyopadhyay, B.</creator><creator>Kane, C.D.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2000</creationdate><title>Neural network based fabric classification and blend composition analysis</title><author>Desai, J.V. ; Bandyopadhyay, B. ; Kane, C.D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i104t-d1998170bbffaf3f9ed28746159992483bf38c1df8d066120d9b4c50ba6b44de3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Artificial neural networks</topic><topic>Fabrics</topic><topic>Knowledge based systems</topic><topic>Mechanical factors</topic><topic>Neural networks</topic><topic>Neurons</topic><topic>Pattern recognition</topic><topic>Radial basis function networks</topic><topic>Textile industry</topic><topic>Textile technology</topic><toplevel>online_resources</toplevel><creatorcontrib>Desai, J.V.</creatorcontrib><creatorcontrib>Bandyopadhyay, B.</creatorcontrib><creatorcontrib>Kane, C.D.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Desai, J.V.</au><au>Bandyopadhyay, B.</au><au>Kane, C.D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Neural network based fabric classification and blend composition analysis</atitle><btitle>Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)</btitle><stitle>ICIT</stitle><date>2000</date><risdate>2000</risdate><volume>2</volume><spage>231</spage><epage>236 vol.1</epage><pages>231-236 vol.1</pages><isbn>9780780358126</isbn><isbn>0780358120</isbn><abstract>Fabric classification plays an important role in the textile industry. Fabrics classification and determining the blend composition involves tedious work and time consumption. Knowledge based systems like artificial neural networks may be successfully employed to over come such problems. In this paper, a method is presented to classify and determine blend composition using neural networks. By inputting the mechanical properties measured from Kawabata evaluation system to the neural network, one can get the desired results. A comparative study in the results is made between the backpropagation and radial basis function algorithms to test the suitability of the same for the proposed textile application.</abstract><pub>IEEE</pub><doi>10.1109/ICIT.2000.854137</doi></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Artificial neural networks Fabrics Knowledge based systems Mechanical factors Neural networks Neurons Pattern recognition Radial basis function networks Textile industry Textile technology |
| title | Neural network based fabric classification and blend composition analysis |
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