{"id":"https://openalex.org/W2121570020","doi":"https://doi.org/10.1109/cvpr.2008.4587380","title":"A learning-based hybrid tagging and browsing approach for efficient manual image annotation","display_name":"A learning-based hybrid tagging and browsing approach for efficient manual image annotation","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2121570020","doi":"https://doi.org/10.1109/cvpr.2008.4587380","mag":"2121570020"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"article","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/A5102917040","display_name":"Rong Yan","orcid":"https://orcid.org/0000-0002-8566-9082"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"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":"Rong Yan","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","IBM T.J. Watson Research Center, Hawthorne, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T.J. Watson Research Center, Hawthorne, NY","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030886753","display_name":"Apostol Natsev","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"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":"Apostol Natsev","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","IBM T.J. Watson Research Center, Hawthorne, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T.J. Watson Research Center, Hawthorne, NY","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045892503","display_name":"Murray Campbell","orcid":"https://orcid.org/0000-0001-8158-894X"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"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":"Murray Campbell","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","IBM T.J. Watson Research Center, Hawthorne, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T.J. Watson Research Center, Hawthorne, NY","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.39,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.96871851,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9997000098228455,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9965999722480774,"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":0.987500011920929,"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/annotation","display_name":"Annotation","score":0.9277917742729187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8110825419425964},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.7501240968704224},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6035868525505066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5015676021575928},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4779417812824249},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4675435423851013},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4254509210586548},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39025071263313293}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.9277917742729187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8110825419425964},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.7501240968704224},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6035868525505066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5015676021575928},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4779417812824249},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4675435423851013},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4254509210586548},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39025071263313293},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2008.4587380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.332.404","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.404","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/040.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1984565341","https://openalex.org/W1994271853","https://openalex.org/W2024368999","https://openalex.org/W2089150756","https://openalex.org/W2103630129","https://openalex.org/W2105071349","https://openalex.org/W2110764733","https://openalex.org/W2115733720","https://openalex.org/W2120369594","https://openalex.org/W2125238156","https://openalex.org/W2137918516","https://openalex.org/W2138079527","https://openalex.org/W2141282920","https://openalex.org/W2181691731","https://openalex.org/W2283195891","https://openalex.org/W2435251607","https://openalex.org/W3021461773","https://openalex.org/W4237065586","https://openalex.org/W4285719527","https://openalex.org/W6628754449","https://openalex.org/W7011438494"],"related_works":["https://openalex.org/W3177930984","https://openalex.org/W2052697133","https://openalex.org/W2119028572","https://openalex.org/W2376984068","https://openalex.org/W2152482390","https://openalex.org/W2365617273","https://openalex.org/W2076896210","https://openalex.org/W2384288472","https://openalex.org/W1539573266","https://openalex.org/W2506386910"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"introduce":[4],"a":[5,28,65,81],"learning":[6],"approach":[7],"to":[8,35,80],"improve":[9],"the":[10,37,56,74],"efficiency":[11],"of":[12,59],"manual":[13,20,44],"image":[14,21],"annotation.":[15],"Although":[16],"important":[17],"in":[18,27,84],"practice,":[19],"annotation":[22,38,45,68,85],"has":[23],"rarely":[24],"been":[25],"studied":[26],"quantitative":[29],"way.":[30],"We":[31],"propose":[32],"formal":[33,52],"models":[34,53],"characterize":[36],"times":[39],"for":[40],"two":[41,61],"commonly":[42],"used":[43],"approaches,":[46,62],"i.e.,":[47],"tagging":[48],"and":[49,63],"browsing.":[50],"The":[51],"make":[54],"clear":[55],"complementary":[57],"properties":[58],"these":[60],"inspire":[64],"learning-based":[66],"hybrid":[67],"algorithm.":[69],"Our":[70],"experiments":[71],"show":[72],"that":[73],"proposed":[75],"algorithm":[76],"can":[77],"achieve":[78],"up":[79],"50%":[82],"reduction":[83],"time":[86],"over":[87],"baseline":[88],"methods.":[89]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}