{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T15:12:37Z","timestamp":1648912357011},"reference-count":26,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2013,1,1]],"date-time":"2013-01-01T00:00:00Z","timestamp":1356998400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"name":"Doctoral Program of Higher Education of China","award":["20122302120072"],"award-info":[{"award-number":["20122302120072"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2013]]},"abstract":"<jats:p>The two-phase test sample representation (TPTSR) was proposed as a useful classifier for face recognition. However, the TPTSR method is not able to reject the impostor, so it should be modified for real-world applications. This paper introduces a thresholded TPTSR (T-TPTSR) method for complex object recognition with outliers, and two criteria for assessing the performance of outlier rejection and member classification are defined. The performance of the T-TPTSR method is compared with the modified global representation, PCA and LDA methods, respectively. The results show that the T-TPTSR method achieves the best performance among them according to the two criteria.<\/jats:p>","DOI":"10.1155\/2013\/248380","type":"journal-article","created":{"date-parts":[[2013,3,11]],"date-time":"2013-03-11T21:00:48Z","timestamp":1363035648000},"page":"1-10","source":"Crossref","is-referenced-by-count":0,"title":["Thresholded Two-Phase Test Sample Representation for Outlier Rejection in Biological Recognition"],"prefix":"10.1155","volume":"2013","author":[{"given":"Xiang","family":"Wu","sequence":"first","affiliation":[{"name":"Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Wu","sequence":"additional","affiliation":[{"name":"Shenzhen Key Lab of Wind Power and Smart Grid, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"98","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/34.41390"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2007.09.021"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.1261097"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1117\/1.3359514"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1155\/2010\/158395"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2011.2152852"},{"key":"7","first-page":"1027","volume":"8","year":"2007","journal-title":"Journal of Machine Learning Research"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/298634"},{"key":"9","first-page":"183","volume":"10","year":"2009","journal-title":"Journal of Machine Learning Research"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(03)00015-7"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2049235"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2010.2044470"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.79"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1016\/j.pnsc.2009.04.013"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/769702"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/549102"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/814356"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/613465"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2012.2217154"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2011.2138790"},{"issue":"3","key":"24","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1364\/JOSAA.4.000519","volume":"4","year":"1987","journal-title":"Journal of the Optical Society of America A"},{"issue":"1","key":"25","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1162\/jocn.1991.3.1.71","volume":"3","year":"1991","journal-title":"Journal of Cognitive Neuroscience"},{"key":"26","year":"2002"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1109\/72.914517"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.884929"},{"issue":"10","key":"30","doi-asserted-by":"crossref","first-page":"1090","DOI":"10.1109\/34.879790","volume":"22","year":"2000","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2013\/248380.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2013\/248380.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2013\/248380.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,21]],"date-time":"2017-06-21T09:10:05Z","timestamp":1498036205000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/cmmm\/2013\/248380\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"references-count":26,"alternative-id":["248380","248380"],"URL":"https:\/\/doi.org\/10.1155\/2013\/248380","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"value":"1748-670X","type":"print"},{"value":"1748-6718","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013]]}}}