{"id":"https://openalex.org/W2150921871","doi":"https://doi.org/10.1186/s13634-015-0224-z","title":"Class-specific Gaussian-multinomial latent Dirichlet allocation for image annotation","display_name":"Class-specific Gaussian-multinomial latent Dirichlet allocation for image annotation","publication_year":2015,"publication_date":"2015-04-30","ids":{"openalex":"https://openalex.org/W2150921871","doi":"https://doi.org/10.1186/s13634-015-0224-z","mag":"2150921871"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-015-0224-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-015-0224-z","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-015-0224-z","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-015-0224-z","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101738810","display_name":"Zhiming Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiming Qian","raw_affiliation_strings":["College of Electronic Science and Engineering, National University of Defense Technology, Deya Road, 410073 Changsha, China","College of Electronic Science and Engineering, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, Deya Road, 410073 Changsha, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079556851","display_name":"Ping Zhong","orcid":"https://orcid.org/0000-0002-8686-3928"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Zhong","raw_affiliation_strings":["College of Electronic Science and Engineering, National University of Defense Technology, Deya Road, 410073 Changsha, China","College of Electronic Science and Engineering, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, Deya Road, 410073 Changsha, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002760019","display_name":"Runsheng Wang","orcid":"https://orcid.org/0000-0002-7514-0767"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runsheng Wang","raw_affiliation_strings":["College of Electronic Science and Engineering, National University of Defense Technology, Deya Road, 410073 Changsha, China","College of Electronic Science and Engineering, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, Deya Road, 410073 Changsha, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"College of Electronic Science and Engineering, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101738810"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08745886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2015","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9990000128746033,"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"}},"topics":[{"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9968000054359436,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9923999905586243,"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/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.8917288780212402},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.702366828918457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.598711371421814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.550732433795929},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5352436304092407},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4669189453125},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.46011003851890564},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.4481116235256195},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.4448685646057129},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.4231416583061218},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.41162168979644775},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3403548002243042},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.33431413769721985},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32273629307746887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2149980068206787},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.17775651812553406}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.8917288780212402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.702366828918457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.598711371421814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.550732433795929},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5352436304092407},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4669189453125},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.46011003851890564},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.4481116235256195},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.4448685646057129},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.4231416583061218},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.41162168979644775},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3403548002243042},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.33431413769721985},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32273629307746887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2149980068206787},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.17775651812553406},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1186/s13634-015-0224-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-015-0224-z","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-015-0224-z","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1186/s13634-015-0224-z","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-015-0224-z","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1186/s13634-015-0224-z","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2805227048","display_name":null,"funder_award_id":"61271439","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2150921871.pdf","grobid_xml":"https://content.openalex.org/works/W2150921871.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1487335190","https://openalex.org/W1503398984","https://openalex.org/W1880262756","https://openalex.org/W1970842225","https://openalex.org/W1978163864","https://openalex.org/W1982821085","https://openalex.org/W1990702921","https://openalex.org/W2004646046","https://openalex.org/W2005070869","https://openalex.org/W2006031689","https://openalex.org/W2020842694","https://openalex.org/W2020903464","https://openalex.org/W2023326407","https://openalex.org/W2027656039","https://openalex.org/W2072509929","https://openalex.org/W2098062695","https://openalex.org/W2102544846","https://openalex.org/W2103537693","https://openalex.org/W2122695597","https://openalex.org/W2126097610","https://openalex.org/W2128361402","https://openalex.org/W2130278361","https://openalex.org/W2130569706","https://openalex.org/W2135533176","https://openalex.org/W2141200867","https://openalex.org/W2141282920","https://openalex.org/W2143583134","https://openalex.org/W2143885292","https://openalex.org/W2145011027","https://openalex.org/W2150692003","https://openalex.org/W2150832512","https://openalex.org/W2154624311","https://openalex.org/W2161561128","https://openalex.org/W2163808566","https://openalex.org/W2164130625","https://openalex.org/W2494048233","https://openalex.org/W2503086503","https://openalex.org/W2536305071","https://openalex.org/W2611015177","https://openalex.org/W6600105257","https://openalex.org/W6600325268","https://openalex.org/W6600669965","https://openalex.org/W6601313673","https://openalex.org/W6604372272","https://openalex.org/W6606042081"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W3005513013","https://openalex.org/W2611137333","https://openalex.org/W4291700620","https://openalex.org/W2529577912"],"abstract_inverted_index":{"Image":[0],"annotation":[1,161,191,206],"has":[2],"been":[3],"a":[4,143],"challenging":[5],"problem":[6,137],"due":[7],"to":[8,23,32,61],"the":[9,19,28,38,63,77,92,109,122,129,135,178,182,195,198],"well-known":[10],"semantic":[11,29,39,93],"gap":[12],"between":[13],"two":[14,189],"heterogeneous":[15],"information":[16],"modalities,":[17],"i.e.,":[18],"visual":[20,25,65,112],"modality":[21,30],"referring":[22,31],"low-level":[24],"features":[26,113],"and":[27,134],"high-level":[33],"human":[34],"concepts.":[35],"To":[36,98],"bridge":[37],"gap,":[40],"we":[41],"present":[42],"an":[43,59,154,163],"extension":[44],"of":[45,70,111,125,131,157,197],"latent":[46,54],"Dirichlet":[47,55],"allocation":[48,56],"(LDA),":[49],"denoted":[50],"as":[51,149],"class-specific":[52],"Gaussian-multinomial":[53],"(csGM-LDA),":[57],"in":[58,160,181],"effort":[60],"simulate":[62],"human's":[64],"perception":[66],"system.":[67],"An":[68],"analysis":[69],"previous":[71],"supervised":[72],"LDA":[73,82],"models":[74,83],"shows":[75],"that":[76],"topics":[78],"discovered":[79],"by":[80,86,104,142,201],"generative":[81],"are":[84],"driven":[85],"general":[87],"image":[88,96,184],"regularities":[89,94],"rather":[90],"than":[91],"for":[95,114,175],"annotation.":[97],"address":[99],"this,":[100],"csGM-LDA":[101,119],"is":[102,173],"introduced":[103],"using":[105],"class":[106],"supervision":[107,127],"at":[108],"level":[110],"multimodal":[115],"topic":[116,126,132],"modeling.":[117],"The":[118],"model":[120],"combines":[121],"labeling":[123],"strength":[124],"with":[128,203],"flexibility":[130],"discovery,":[133],"modeling":[136],"can":[138],"be":[139],"effectively":[140],"solved":[141],"variational":[144],"expectation-maximization":[145],"(EM)":[146],"algorithm.":[147],"Moreover,":[148],"natural":[150],"images":[151],"usually":[152],"generate":[153],"enormous":[155],"size":[156],"high-dimensional":[158],"data":[159],"applications,":[162],"efficient":[164],"descriptor":[165],"based":[166],"on":[167,188],"Laplacian":[168],"regularized":[169],"uncorrelated":[170],"tensor":[171],"representation":[172],"proposed":[174,199],"explicitly":[176],"exploiting":[177],"manifold":[179],"structures":[180],"high-order":[183],"space.":[185],"Experimental":[186],"results":[187],"standard":[190],"datasets":[192],"have":[193],"shown":[194],"effectiveness":[196],"method":[200],"comparing":[202],"several":[204],"state-of-the-art":[205],"methods.":[207]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
