{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T02:48:58Z","timestamp":1773456538436,"version":"3.50.1"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/100002418","name":"Intel Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100002418","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Automat. Sci. Eng."],"published-print":{"date-parts":[[2018,1]]},"DOI":"10.1109\/tase.2016.2594288","type":"journal-article","created":{"date-parts":[[2016,8,31]],"date-time":"2016-08-31T16:35:27Z","timestamp":1472661327000},"page":"145-159","source":"Crossref","is-referenced-by-count":41,"title":["Multifeature, Sparse-Based Approach for Defects Detection and Classification in Semiconductor Units"],"prefix":"10.1109","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7206-2620","authenticated-orcid":false,"given":"Bashar M.","family":"Haddad","sequence":"first","affiliation":[]},{"given":"Sen","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Lina J.","family":"Karam","sequence":"additional","affiliation":[]},{"given":"Jieping","family":"Ye","sequence":"additional","affiliation":[]},{"given":"Nital S.","family":"Patel","sequence":"additional","affiliation":[]},{"given":"Martin W.","family":"Braun","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/1007730.1007733"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1997.1504"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2011.2161285"},{"key":"ref32","first-page":"554","article-title":"How to make stacking better and faster while also taking care of an unknown weakness","author":"seewald","year":"2002","journal-title":"Proc 19th Int Conf Mach Learn"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1613\/jair.594","article-title":"Issues in stacked generalization","volume":"10","author":"ting","year":"1999","journal-title":"J Artif Intell Res"},{"key":"ref30","article-title":"Towards understanding stacking-studies of a general ensemble learning scheme","author":"seewald","year":"2003"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/1007730.1007735"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.95"},{"key":"ref35","first-page":"204","article-title":"Learning and making decisions when costs and probabilities are both unknown","author":"zadrozny","year":"2013","journal-title":"Proc 6th ACM SIGKDD Int Conf Knowl Discovery Data Mining"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/BF00153762"},{"key":"ref60","first-page":"747","article-title":"BoF meets HOG: Feature extraction based on histograms of oriented p.d.f. gradients for image classification","author":"kobayashi","year":"2013","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2001.990517"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1016218223"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.251"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.433"},{"key":"ref29","first-page":"367","article-title":"Stacking bagged and dagged models","author":"ting","year":"1997","journal-title":"Proc 14th Int Conf Mach Learn"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ISSM.1995.524362"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/B978-012554157-2\/50001-8"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref22","first-page":"1077","article-title":"Linear dimensionality reduction for multi-label classification","author":"ji","year":"2009","journal-title":"Proc Intern Joint Conf Artificial Intel (IJCAI)"},{"key":"ref21","author":"simonyan","year":"2014","journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540018"},{"key":"ref23","first-page":"1794","article-title":"Linear spatial pyramid matching using sparse coding for image classification","author":"yang","year":"2009","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref26","first-page":"111","article-title":"A theoretical analysis of feature pooling in visual recognition","author":"boureau","year":"2010","journal-title":"Proc 27th Int Conf Mach Learn"},{"key":"ref25","author":"liu","year":"2009","journal-title":"SLEP Sparse Learning with Efficient Projections"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1002\/sam.10061"},{"key":"ref51","first-page":"107","article-title":"SMOTEBoost: Improving prediction of the minority class in boosting","author":"chawla","year":"2003","journal-title":"Proc of Conf on Knowledge Discovery in Data"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.413"},{"key":"ref58","first-page":"1315","article-title":"Ensemble pruning via semi-definite programming","volume":"7","author":"zhang","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-014-0303-8"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2313638"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.02.056"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2013.2281820"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCA.2009.2029559"},{"key":"ref52","first-page":"3133","article-title":"Do we need hundreds of classifiers to solve real world classification problems?","volume":"15","author":"fern\u00e1ndez-delgado","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref10","article-title":"A versatile automated defect detection and classification system for assembly, test semi-conductor manufacturing","author":"said","year":"0"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2004.823819"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-008-0087-0"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"ref13","first-page":"831","article-title":"Shape context: A new descriptor for shape matching and object recognition","author":"belongie","year":"2000","journal-title":"Proc NIPS"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.167"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2007.383198"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.320"},{"key":"ref18","first-page":"1","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6638959"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref3","article-title":"Method and apparatus for incremental concurrent learning in automatic semiconductor wafer and liquid crystal display defect classification","author":"lee","year":"2000"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(05)80023-1"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2010.2044470"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1996.10476733"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/BF00117832"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCA.2010.2084081"},{"key":"ref9","first-page":"1","article-title":"Super learner","volume":"6","author":"laan","year":"2007","journal-title":"Statistical Appl Genetics Molecular Biol"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/WCSE.2009.756"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-01307-2_43"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CIDM.2009.4938667"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"SMOTE: Synthetic minority over-sampling technique","volume":"16","author":"chawla","year":"2002","journal-title":"J Artif Intell Res"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-74553-2_28"},{"key":"ref44","first-page":"1322","article-title":"ADASYN: Adaptive synthetic sampling approach for imbalanced learning","author":"he","year":"2008","journal-title":"Proc IEEE Int Conf Neural Netw"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/11538059_91"}],"container-title":["IEEE Transactions on Automation Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8856\/8246664\/07557053.pdf?arnumber=7557053","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:41:47Z","timestamp":1641987707000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7557053\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,1]]},"references-count":62,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tase.2016.2594288","relation":{},"ISSN":["1545-5955","1558-3783"],"issn-type":[{"value":"1545-5955","type":"print"},{"value":"1558-3783","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,1]]}}}