{"id":"https://openalex.org/W2161177789","doi":"https://doi.org/10.1109/icme.2002.1035658","title":"BPMs versus SVMs for image classification","display_name":"BPMs versus SVMs for image classification","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2161177789","doi":"https://doi.org/10.1109/icme.2002.1035658","mag":"2161177789"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2002.1035658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2002.1035658","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Conference on Multimedia and Expo","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108047817","display_name":"Gang Wu","orcid":"https://orcid.org/0009-0007-9599-4341"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Santa Barbara, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Santa Barbara, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013545831","display_name":"Edward Yi Chang","orcid":"https://orcid.org/0000-0003-1616-5240"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"E. Chang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Santa Barbara, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Santa Barbara, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024756743","display_name":"Chung\u2010Sheng Li","orcid":"https://orcid.org/0000-0001-9072-1140"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chung-Sheng Li","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Hawthorne, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.47,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63172861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"505","last_page":"508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.9095218777656555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.724185585975647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7184651494026184},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6769930720329285},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6110984683036804},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5850495100021362},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5787544250488281},{"id":"https://openalex.org/keywords/structured-support-vector-machine","display_name":"Structured support vector machine","score":0.5488128066062927},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5190987586975098},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5093098878860474},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4786318838596344},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1401999592781067},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.059481263160705566}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.9095218777656555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.724185585975647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7184651494026184},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6769930720329285},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6110984683036804},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5850495100021362},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5787544250488281},{"id":"https://openalex.org/C125168437","wikidata":"https://www.wikidata.org/wiki/Q7625184","display_name":"Structured support vector machine","level":3,"score":0.5488128066062927},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5190987586975098},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5093098878860474},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4786318838596344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1401999592781067},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.059481263160705566},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2002.1035658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2002.1035658","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Conference on Multimedia and Expo","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1583555936","https://openalex.org/W1588229727","https://openalex.org/W1966522529","https://openalex.org/W2087347434","https://openalex.org/W2095584394","https://openalex.org/W2119821739","https://openalex.org/W2126291774","https://openalex.org/W2148603752","https://openalex.org/W2156909104","https://openalex.org/W2158001550","https://openalex.org/W2544511689","https://openalex.org/W2904258669","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W6635224348","https://openalex.org/W6729378523","https://openalex.org/W7075645260"],"related_works":["https://openalex.org/W1948992892","https://openalex.org/W2186666570","https://openalex.org/W2104936869","https://openalex.org/W2143867687","https://openalex.org/W4253128984","https://openalex.org/W2384390720","https://openalex.org/W2122277321","https://openalex.org/W2565312173","https://openalex.org/W2364362706","https://openalex.org/W2104406636"],"abstract_inverted_index":{"The":[0],"Bayes":[1],"point":[2],"machine":[3,18],"(BPM)":[4],"has":[5],"been":[6],"demonstrated":[7],"theoretically":[8],"to":[9],"have":[10],"better":[11],"learning":[12],"ability":[13],"than":[14],"the":[15,33,36,39,48,54,67,70],"support":[16],"vector":[17],"(SVM).":[19],"We":[20,30,45],"describe":[21],"these":[22],"two":[23],"machines":[24],"and":[25,38],"tell":[26],"how":[27],"they":[28],"differ.":[29],"empirically":[31],"compare":[32],"performance":[34],"of":[35],"BPM":[37,71],"SVM":[40,49],"on":[41],"an":[42],"image":[43,55],"dataset.":[44],"conclude":[46],"that":[47,69],"is":[50],"more":[51],"attractive":[52],"for":[53],"classification":[56,75],"task":[57],"because":[58],"it":[59],"requires":[60],"a":[61],"much":[62],"shorter":[63],"training":[64],"time,":[65],"despite":[66],"fact":[68],"achieves":[72],"slightly":[73],"higher":[74],"accuracy.":[76]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}