{"id":"https://openalex.org/W1021336285","doi":null,"title":"Automatic Image Annotation Using Semi-Supervised Multi-Instance Multi-Label Learning Algorithm","display_name":"Automatic Image Annotation Using Semi-Supervised Multi-Instance Multi-Label Learning Algorithm","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W1021336285","mag":"1021336285"},"language":"en","primary_location":{"id":"mag:1021336285","doi":null,"is_oa":false,"landing_page_url":"http://ir.ia.ac.cn/handle/173211/20393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5085406955","display_name":"Songhe Feng","orcid":"https://orcid.org/0000-0002-5922-9358","observed_orcids":["https://orcid.org/0000-0002-5922-9358"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160505950","display_name":"Songhe","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Songhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160430628","display_name":"Xu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160402674","display_name":"\ufffd. Lang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"\ufffd. Lang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160560735","display_name":"Congyan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Congyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5160393140","display_name":"Li","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"4","first_page":"602","last_page":"606"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9940999746322632,"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":0.9940999746322632,"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":0.0034000000450760126,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.0010000000474974513,"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/automatic-image-annotation","display_name":"automatic image annotation","score":0.984000027179718},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"semi-supervised learning","score":0.8899999856948853},{"id":"https://openalex.org/keywords/multiple-instance-learning","display_name":"multiple instance learning","score":0.968999981880188},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"multi-label classification","score":0.996999979019165},{"id":"https://openalex.org/keywords/gaussian-mixture-model","display_name":"Gaussian mixture model","score":0.8669999837875366},{"id":"https://openalex.org/keywords/manifold-ranking","display_name":"manifold ranking","score":0.7129999995231628},{"id":"https://openalex.org/keywords/label-propagation","display_name":"label propagation","score":0.6840000152587891},{"id":"https://openalex.org/keywords/unlabeled-data","display_name":"unlabeled data","score":0.7300000190734863},{"id":"https://openalex.org/keywords/feature-mapping","display_name":"feature mapping","score":0.5040000081062317},{"id":"https://openalex.org/keywords/corel-image-dataset","display_name":"Corel image dataset","score":0.6039999723434448}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6961241960525513},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6548332571983337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6120957136154175},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.5843404531478882},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5802755951881409},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5401669144630432},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5279542207717896},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.48048487305641174},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4744628071784973},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4727177023887634},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4669680893421173},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4558213949203491},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.455070436000824},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4355359673500061},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"mag:1021336285","doi":null,"is_oa":false,"landing_page_url":"http://ir.ia.ac.cn/handle/173211/20393","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"mag:3143085055","doi":null,"is_oa":false,"landing_page_url":"http://www.cqvip.com/qk/86774X/200804/28662706.html","pdf_url":null,"source":{"id":"https://openalex.org/S144330684","display_name":"Chinese Journal of Electronics","issn_l":"1022-4653","issn":["1022-4653","2075-5597"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","norway-1","oarl","poland-40","russia-white-list-3"],"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"\u7535\u5b50\u5b66\u62a5\uff1a\u82f1\u6587\u7248","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1972352301","https://openalex.org/W1985881688","https://openalex.org/W2102468157","https://openalex.org/W2538497170","https://openalex.org/W2074633073","https://openalex.org/W2121855020","https://openalex.org/W2401353841","https://openalex.org/W22123982","https://openalex.org/W7097096454","https://openalex.org/W9480776"],"abstract_inverted_index":{"Automatic":[0],"image":[1,32,192],"annotation":[2,17,74,193],"has":[3],"emerged":[4],"as":[5,44],"an":[6,31],"important":[7],"research":[8],"topic.":[9],"From":[10],"the":[11,16,28,73,87,104,110,119,127,159,168,180,186],"perspective":[12],"of":[13,35,65],"machine":[14],"learning,":[15],"task":[18],"fits":[19],"both":[20,66,98,133],"multi-instance":[21,54],"and":[22,38,68,100,135],"multi-label":[23,55],"learning":[24,57],"framework":[25],"due":[26],"to":[27,71,85,93,117,166,174],"fact":[29],"that":[30,158,185],"is":[33,39,82],"composed":[34],"multiple":[36,42],"regions,":[37],"as-sociated":[40],"with":[41,91],"keywords":[43],"well.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49],"propose":[50],"a":[51,77,94,131,141],"novel":[52,142],"Semi-supervised":[53],"(SSMIML)":[56],"framework,":[58],"which":[59],"aims":[60],"at":[61],"taking":[62],"full":[63],"advantage":[64],"labeled":[67],"unlabeled":[69,101,136,175],"data":[70,182],"address":[72],"problem.":[75],"Specifically,":[76],"reinforced":[78],"diverse":[79],"density":[80,122],"algorithm":[81,161],"applied":[83],"firstly":[84],"select":[86],"Instance":[88],"prototypes":[89],"(IPs)":[90],"respect":[92],"given":[95],"keyword":[96],"from":[97,171],"positive":[99,134,172],"bags.":[102],"Then,":[103],"selected":[105],"IPs":[106],"are":[107,138],"modeled":[108],"using":[109,140],"Gaussian":[111],"mixture":[112],"model":[113],"(GMM)":[114],"in":[115],"order":[116],"reflect":[118],"semantic":[120],"class":[121,128],"distribution.":[123],"Furthermore,":[124],"based":[125],"on":[126,179],"distribution":[129],"for":[130],"keyword,":[132],"bags":[137,173,176],"redefined":[139],"feature":[143,155],"mapping":[144],"strategy.":[145],"Thus,":[146],"each":[147],"bag":[148],"can":[149,162],"be":[150,163],"represented":[151],"by":[152],"one":[153],"fixed-length":[154],"vector":[156],"so":[157],"manifold-ranking":[160],"used":[164],"subsequently":[165],"propagate":[167],"corresponding":[169],"label":[170],"directly.":[177],"Experiments":[178],"Corel":[181],"set":[183],"show":[184],"proposed":[187],"method":[188],"outperforms":[189],"most":[190],"existing":[191],"algorithms.":[194]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2016-06-24T00:00:00"}