{"id":"https://openalex.org/W2087655037","doi":"https://doi.org/10.1145/2072298.2072019","title":"Ensemble approach based on conditional random field for multi-label image and video annotation","display_name":"Ensemble approach based on conditional random field for multi-label image and video annotation","publication_year":2011,"publication_date":"2011-11-28","ids":{"openalex":"https://openalex.org/W2087655037","doi":"https://doi.org/10.1145/2072298.2072019","mag":"2087655037"},"language":"en","primary_location":{"id":"doi:10.1145/2072298.2072019","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2072298.2072019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM international conference on Multimedia","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/A5086235570","display_name":"Xin-Shun Xu","orcid":"https://orcid.org/0000-0001-9972-7370"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin-Shun Xu","raw_affiliation_strings":["Shandong University &amp; Nanjing University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong University &amp; Nanjing University, Jinan, China","institution_ids":["https://openalex.org/I154099455","https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104044152","display_name":"Yuan Jiang","orcid":"https://orcid.org/0009-0009-8093-4826"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Jiang","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100612023","display_name":"Liang Peng","orcid":"https://orcid.org/0000-0002-9831-2787"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Peng","raw_affiliation_strings":["Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003418019","display_name":"Xiangyang Xue","orcid":"https://orcid.org/0000-0002-4897-9209"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyang Xue","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100621138","display_name":"Zhi\u2010Hua Zhou","orcid":"https://orcid.org/0000-0003-0746-1494"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi-Hua Zhou","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5086235570"],"corresponding_institution_ids":["https://openalex.org/I154099455","https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":3.0817,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.92033779,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1377","last_page":"1380"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9990000128746033,"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/conditional-random-field","display_name":"Conditional random field","score":0.9213558435440063},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8115589618682861},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7236906290054321},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6250137090682983},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5938142538070679},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5736019015312195},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5558861494064331},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5485308170318604},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5400860905647278},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5270212888717651},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5025906562805176},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4615708589553833},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.4482805132865906},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37693262100219727},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32733142375946045},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.2661339044570923},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08958417177200317}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.9213558435440063},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8115589618682861},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7236906290054321},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6250137090682983},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5938142538070679},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5736019015312195},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5558861494064331},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5485308170318604},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5400860905647278},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5270212888717651},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5025906562805176},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4615708589553833},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.4482805132865906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37693262100219727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32733142375946045},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.2661339044570923},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08958417177200317},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2072298.2072019","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2072298.2072019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM international conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.672.6110","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.672.6110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/mm11a.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":39,"referenced_works":["https://openalex.org/W115432069","https://openalex.org/W1484654248","https://openalex.org/W1535599202","https://openalex.org/W1877469910","https://openalex.org/W1999182238","https://openalex.org/W2004646046","https://openalex.org/W2023316690","https://openalex.org/W2025051526","https://openalex.org/W2052684427","https://openalex.org/W2053463056","https://openalex.org/W2058839679","https://openalex.org/W2094067871","https://openalex.org/W2104252248","https://openalex.org/W2104978738","https://openalex.org/W2112020727","https://openalex.org/W2115439269","https://openalex.org/W2116608170","https://openalex.org/W2119466907","https://openalex.org/W2125238156","https://openalex.org/W2126017203","https://openalex.org/W2127411609","https://openalex.org/W2135533176","https://openalex.org/W2136507825","https://openalex.org/W2137918516","https://openalex.org/W2146241755","https://openalex.org/W2147880316","https://openalex.org/W2156336347","https://openalex.org/W2162762921","https://openalex.org/W2164736477","https://openalex.org/W2171881030","https://openalex.org/W2536305071","https://openalex.org/W2917011293","https://openalex.org/W4241005218","https://openalex.org/W6629011444","https://openalex.org/W6631929218","https://openalex.org/W6656422882","https://openalex.org/W6678852649","https://openalex.org/W6759319768","https://openalex.org/W6759836896"],"related_works":["https://openalex.org/W151193258","https://openalex.org/W1607472309","https://openalex.org/W2954843021","https://openalex.org/W2947903144","https://openalex.org/W2006147162","https://openalex.org/W2547852346","https://openalex.org/W2126384842","https://openalex.org/W2803007456","https://openalex.org/W3150234497","https://openalex.org/W2295398630"],"abstract_inverted_index":{"Multi-label":[0],"image/video":[1],"annotation":[2,29,41],"is":[3,24,117],"a":[4,21,97],"challenging":[5],"task":[6],"that":[7,113],"allows":[8],"to":[9,50,122],"correlate":[10],"more":[11],"than":[12],"one":[13],"high-level":[14],"semantic":[15],"keyword":[16],"with":[17,31],"an":[18],"image/video-clip.":[19],"Previously,":[20],"single":[22],"model":[23],"usually":[25],"used":[26],"for":[27,80],"the":[28,40,52,57,63,84,90,114],"task,":[30],"relatively":[32],"large":[33],"variance":[34,54],"in":[35],"performance.":[36],"The":[37],"correlation":[38,58],"among":[39],"keywords":[42,93],"should":[43],"also":[44],"be":[45],"considered.":[46],"In":[47,72],"this":[48,73],"paper,":[49],"reduce":[51],"performance":[53],"and":[55,89,109],"exploit":[56],"between":[59,92],"keywords,":[60],"we":[61],"propose":[62],"En-CRF":[64,115],"(Ensemble":[65],"based":[66],"on":[67,103],"Conditional":[68],"Random":[69],"Field)":[70],"method.":[71],"method,":[74],"multiple":[75],"models":[76,88],"are":[77,94],"first":[78],"trained":[79],"each":[81],"keyword,":[82],"then":[83],"predictions":[85],"of":[86],"these":[87],"correlations":[91],"incorporated":[95],"into":[96],"conditional":[98],"random":[99],"field.":[100],"Experimental":[101],"results":[102],"benchmark":[104],"data":[105],"set,":[106],"including":[107],"Corel5k":[108],"TRECVID":[110],"2005,":[111],"show":[112],"method":[116],"superior":[118],"or":[119],"highly":[120],"competitive":[121],"several":[123],"state-of-the-art":[124],"methods.":[125]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
