{"id":"https://openalex.org/W2182206995","doi":"https://doi.org/10.1109/acii.2015.7344679","title":"Neural conditional ordinal random fields for agreement level estimation","display_name":"Neural conditional ordinal random fields for agreement level estimation","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2182206995","doi":"https://doi.org/10.1109/acii.2015.7344679","mag":"2182206995"},"language":"en","primary_location":{"id":"doi:10.1109/acii.2015.7344679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2015.7344679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ris.utwente.nl/ws/files/5380256/Pantic_Neural_Conditional_Ordinal_Random_Fields_for_Agreement.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017568280","display_name":"Nemanja Rakicevic","orcid":"https://orcid.org/0000-0003-3323-2193"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Nemanja Rakicevic","raw_affiliation_strings":["Department of Computing, Imperial College London"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038571306","display_name":"Ognjen Rudovic","orcid":"https://orcid.org/0000-0003-1165-6075"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ognjen Rudovic","raw_affiliation_strings":["Department of Computing, Imperial College London"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009475700","display_name":"Stavros Petridis","orcid":"https://orcid.org/0000-0001-7478-9479"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stavros Petridis","raw_affiliation_strings":["Department of Computing, Imperial College London"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Imperial College London","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016033078","display_name":"Maja Panti\u0107","orcid":"https://orcid.org/0000-0002-3620-5986"},"institutions":[{"id":"https://openalex.org/I124357947","display_name":"University of London","ror":"https://ror.org/04cw6st05","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]},{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["GB","NL"],"is_corresponding":false,"raw_author_name":"Maja Pantic","raw_affiliation_strings":["Department of Computing Imperial College London, University of Twente"],"affiliations":[{"raw_affiliation_string":"Department of Computing Imperial College London, University of Twente","institution_ids":["https://openalex.org/I94624287","https://openalex.org/I45129253","https://openalex.org/I124357947","https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5017568280"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.4451,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77458418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"885","last_page":"890"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.978600025177002,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.978600025177002,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6257066130638123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5958903431892395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5886462330818176},{"id":"https://openalex.org/keywords/ordinal-regression","display_name":"Ordinal regression","score":0.5659119486808777},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5044208765029907},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.4904038906097412},{"id":"https://openalex.org/keywords/ordinal-data","display_name":"Ordinal data","score":0.4898383319377899},{"id":"https://openalex.org/keywords/agreement","display_name":"Agreement","score":0.46723705530166626},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45993709564208984},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42659425735473633},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.41772234439849854},{"id":"https://openalex.org/keywords/intensity","display_name":"Intensity (physics)","score":0.4144602119922638},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4122937321662903},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34574180841445923},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2657771706581116},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07363533973693848}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6257066130638123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5958903431892395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5886462330818176},{"id":"https://openalex.org/C110313322","wikidata":"https://www.wikidata.org/wiki/Q7100793","display_name":"Ordinal regression","level":2,"score":0.5659119486808777},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5044208765029907},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.4904038906097412},{"id":"https://openalex.org/C85461838","wikidata":"https://www.wikidata.org/wiki/Q7100785","display_name":"Ordinal data","level":2,"score":0.4898383319377899},{"id":"https://openalex.org/C2776818064","wikidata":"https://www.wikidata.org/wiki/Q829903","display_name":"Agreement","level":2,"score":0.46723705530166626},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45993709564208984},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42659425735473633},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.41772234439849854},{"id":"https://openalex.org/C93038891","wikidata":"https://www.wikidata.org/wiki/Q1061524","display_name":"Intensity (physics)","level":2,"score":0.4144602119922638},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4122937321662903},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34574180841445923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2657771706581116},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07363533973693848},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/acii.2015.7344679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2015.7344679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-article"},{"id":"pmh:oai:ris.utwente.nl:publications/feb88bb5-7982-43f8-9435-9d5689982bab","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/feb88bb5-7982-43f8-9435-9d5689982bab","pdf_url":"https://ris.utwente.nl/ws/files/5380256/Pantic_Neural_Conditional_Ordinal_Random_Fields_for_Agreement.pdf","source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Rakicevic, N, Rudovic, O & Petridis, S 2015, Neural Conditional Ordinal Random Fields for Agreement Level Estimation. in N Rakicevic, O Rudovic, S Petrids & M Pantic (eds), Proceedings of the International Conference on Affective Computing and Intelligent Interaction (ACII 2015). IEEE, USA, pp. 885-890, 6th International Conference on Affective Computing and Intelligent Interaction, ACII 2015, Xi'an, China, 21/09/15. https://doi.org/10.1109/ACII.2015.7344679","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.704.557","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.704.557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ibug.doc.ic.ac.uk/media/uploads/documents/wasa_nr_final.pdf","raw_type":"text"},{"id":"pmh:oai:ris.utwente.nl:publications/feb88bb5-7982-43f8-9435-9d5689982bab","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:ris.utwente.nl:publications/feb88bb5-7982-43f8-9435-9d5689982bab","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/feb88bb5-7982-43f8-9435-9d5689982bab","pdf_url":"https://ris.utwente.nl/ws/files/5380256/Pantic_Neural_Conditional_Ordinal_Random_Fields_for_Agreement.pdf","source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Rakicevic, N, Rudovic, O & Petridis, S 2015, Neural Conditional Ordinal Random Fields for Agreement Level Estimation. in N Rakicevic, O Rudovic, S Petrids & M Pantic (eds), Proceedings of the International Conference on Affective Computing and Intelligent Interaction (ACII 2015). IEEE, USA, pp. 885-890, 6th International Conference on Affective Computing and Intelligent Interaction, ACII 2015, Xi'an, China, 21/09/15. https://doi.org/10.1109/ACII.2015.7344679","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G8203822267","display_name":null,"funder_award_id":"645094","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2182206995.pdf","grobid_xml":"https://content.openalex.org/works/W2182206995.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W155718687","https://openalex.org/W1491036874","https://openalex.org/W1498436455","https://openalex.org/W1506225903","https://openalex.org/W1560729591","https://openalex.org/W1769825162","https://openalex.org/W1903399393","https://openalex.org/W2002806284","https://openalex.org/W2006047855","https://openalex.org/W2079373094","https://openalex.org/W2083261637","https://openalex.org/W2083261714","https://openalex.org/W2098615198","https://openalex.org/W2101545465","https://openalex.org/W2102800123","https://openalex.org/W2121684305","https://openalex.org/W2126131681","https://openalex.org/W2132024850","https://openalex.org/W2141403362","https://openalex.org/W2142575466","https://openalex.org/W2145316937","https://openalex.org/W2145747781","https://openalex.org/W2147880316","https://openalex.org/W2153635508","https://openalex.org/W2161354826","https://openalex.org/W2170849838","https://openalex.org/W2172279486","https://openalex.org/W2291168657","https://openalex.org/W2291496554","https://openalex.org/W2322584079","https://openalex.org/W4285719527","https://openalex.org/W6633724138","https://openalex.org/W6678583454","https://openalex.org/W6681169319","https://openalex.org/W6681973233","https://openalex.org/W6682082992","https://openalex.org/W6683791313","https://openalex.org/W6685278535","https://openalex.org/W6696688299"],"related_works":["https://openalex.org/W4300104397","https://openalex.org/W2798701209","https://openalex.org/W2912776266","https://openalex.org/W4236496007","https://openalex.org/W1539030525","https://openalex.org/W4237346635","https://openalex.org/W1572610764","https://openalex.org/W2568280491","https://openalex.org/W2963953154","https://openalex.org/W2116853241"],"abstract_inverted_index":{"We":[0,107],"present":[1],"a":[2,65,74],"novel":[3,75],"approach":[4,115],"to":[5],"automated":[6],"estimation":[7],"of":[8,24,38,56,64,93,121,135],"agreement":[9,39,50,58,105,136],"intensity":[10,40,134],"levels":[11,41,59],"from":[12,87,141],"facial":[13,32,142],"images.":[14],"To":[15],"this":[16],"end,":[17],"we":[18,72],"employ":[19],"the":[20,31,43,57,91,104,113,133,148],"MAHNOB":[21],"Mimicry":[22],"database":[23],"subjects":[25,130],"recorded":[26],"during":[27],"dyadic":[28],"interactions,":[29],"where":[30],"images":[33,89,143],"are":[34],"annotated":[35],"in":[36,109],"terms":[37],"using":[42,90,147],"Likert":[44],"scale":[45],"(strong":[46],"disagreement,":[47,48],"neutral,":[49],"and":[51,100],"strong":[52],"agreement).":[53],"Dynamic":[54],"modelling":[55,98,120],"is":[60],"accomplished":[61],"by":[62],"means":[63],"Conditional":[66,77],"Ordinal":[67,78],"Random":[68,79],"Field":[69,80],"model.":[70],"Specifically,":[71],"propose":[73],"Neural":[76,94],"model":[81],"that":[82,112,132],"performs":[83],"non-linear":[84],"feature":[85],"extraction":[86],"face":[88],"notion":[92],"Networks,":[95],"while":[96],"also":[97],"temporal":[99],"ordinal":[101],"relationships":[102],"between":[103],"levels.":[106],"show":[108],"our":[110],"experiments":[111],"proposed":[114,149],"outperforms":[116],"existing":[117],"methods":[118],"for":[119],"sequential":[122],"data.":[123],"The":[124],"preliminary":[125],"results":[126],"obtained":[127],"on":[128],"five":[129],"demonstrate":[131],"can":[137],"successfully":[138],"be":[139],"estimated":[140],"(39%":[144],"F1":[145],"score)":[146],"method.":[150]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}