{"id":"https://openalex.org/W2026121273","doi":"https://doi.org/10.1109/icip.2011.6115605","title":"Boosting global scene classification accuracy by discriminative region localization","display_name":"Boosting global scene classification accuracy by discriminative region localization","publication_year":2011,"publication_date":"2011-09-01","ids":{"openalex":"https://openalex.org/W2026121273","doi":"https://doi.org/10.1109/icip.2011.6115605","mag":"2026121273"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2011.6115605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2011.6115605","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 18th IEEE International Conference on Image Processing","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/A5111656429","display_name":"Thanh Due Ngo","orcid":null},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I200475212","display_name":"The Graduate University for Advanced Studies, SOKENDAI","ror":"https://ror.org/0516ah480","country_code":"JP","type":"education","lineage":["https://openalex.org/I200475212"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Thanh Due Ngo","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan","The Graduate University for Advanced Studies, Sokendai, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"The Graduate University for Advanced Studies, Sokendai, Japan","institution_ids":["https://openalex.org/I200475212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043063578","display_name":"Duy-Dinh Le","orcid":"https://orcid.org/0000-0003-0356-5501"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I200475212","display_name":"The Graduate University for Advanced Studies, SOKENDAI","ror":"https://ror.org/0516ah480","country_code":"JP","type":"education","lineage":["https://openalex.org/I200475212"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Duy-Dinh Le","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan","The Graduate University for Advanced Studies, Sokendai, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"The Graduate University for Advanced Studies, Sokendai, Japan","institution_ids":["https://openalex.org/I200475212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102743927","display_name":"Shin\u2019ichi Satoh","orcid":"https://orcid.org/0000-0001-6995-6447"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I200475212","display_name":"The Graduate University for Advanced Studies, SOKENDAI","ror":"https://ror.org/0516ah480","country_code":"JP","type":"education","lineage":["https://openalex.org/I200475212"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shin'ichi Satoh","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan","The Graduate University for Advanced Studies, Sokendai, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"The Graduate University for Advanced Studies, Sokendai, Japan","institution_ids":["https://openalex.org/I200475212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"1053","last_page":"1056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":1.0,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.9513691663742065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8451127409934998},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7398635149002075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.717056930065155},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6996838450431824},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6757330298423767},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6293470859527588},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5845090746879578},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5217231512069702},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5116401314735413},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4705253839492798},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4385712742805481},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3397533893585205},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.059106260538101196}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9513691663742065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8451127409934998},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7398635149002075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.717056930065155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6996838450431824},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6757330298423767},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6293470859527588},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5845090746879578},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5217231512069702},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5116401314735413},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4705253839492798},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4385712742805481},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3397533893585205},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.059106260538101196},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2011.6115605","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2011.6115605","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 18th IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2097018403","https://openalex.org/W2098166271","https://openalex.org/W2112343299","https://openalex.org/W2136595724","https://openalex.org/W2162915993","https://openalex.org/W2164816523","https://openalex.org/W2534457893","https://openalex.org/W4230699754","https://openalex.org/W4232730838","https://openalex.org/W6674642818","https://openalex.org/W6680240620","https://openalex.org/W6684392622"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W2116862786","https://openalex.org/W4390721878","https://openalex.org/W2963610131","https://openalex.org/W2761785940","https://openalex.org/W2129933262"],"abstract_inverted_index":{"Combining":[0],"global":[1,93],"scene":[2,94],"classification":[3,12,95,102,146],"with":[4,60,96],"object":[5,17,27,34,42,50,78],"detection":[6,79],"has":[7],"helped":[8],"in":[9,63,80],"improving":[10],"the":[11,33,38,41,48,64,81,118,129,136,141,145],"accuracy.":[13,120],"However,":[14],"training":[15],"an":[16],"detector":[18,28],"requires":[19],"a":[20,88,105],"large":[21],"amount":[22],"of":[23,40,54,77],"manual":[24],"annotation.":[25],"The":[26],"may":[29],"also":[30],"fail":[31],"when":[32],"is":[35,43,85],"occluded.":[36],"Meanwhile,":[37],"presence":[39],"not":[44],"only":[45],"indicated":[46],"by":[47],"entire":[49],"region":[51,74,98,109,132],"but":[52],"any":[53],"its":[55,58],"parts":[56],"or":[57],"correlations":[59],"other":[61],"regions":[62],"image.":[65],"To":[66],"overcome":[67],"these":[68],"limitations,":[69],"we":[70],"propose":[71],"using":[72],"discriminative":[73,97,108,131],"localization":[75,99,110,133],"instead":[76],"combination.":[82],"Our":[83,121],"contribution":[84],"two-fold,":[86],"a)":[87],"complete":[89],"framework":[90],"that":[91,112,128],"combines":[92],"for":[100],"image":[101],"and":[103],"b)":[104],"weakly":[106],"supervised":[107],"approach":[111,134],"utilizes":[113],"spatial":[114],"context":[115],"to":[116],"improve":[117],"learning":[119],"experimental":[122],"results":[123],"on":[124],"benchmark":[125],"datasets":[126],"demonstrated":[127],"proposed":[130],"outperforms":[135],"state-of-the-art":[137],"approach.":[138],"In":[139],"addition,":[140],"combination":[142],"significantly":[143],"increases":[144],"performance.":[147]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}