{"id":"https://openalex.org/W4220777725","doi":"https://doi.org/10.1109/tpami.2022.3156885","title":"Deep Order-Preserving Learning With Adaptive Optimal Transport Distance","display_name":"Deep Order-Preserving Learning With Adaptive Optimal Transport Distance","publication_year":2022,"publication_date":"2022-03-07","ids":{"openalex":"https://openalex.org/W4220777725","doi":"https://doi.org/10.1109/tpami.2022.3156885","pmid":"https://pubmed.ncbi.nlm.nih.gov/35254972"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3156885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3156885","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ali Akbari","orcid":"https://orcid.org/0000-0003-1457-2977"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ali Akbari","raw_affiliation_strings":["Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K"],"raw_orcid":"https://orcid.org/0000-0003-1457-2977","affiliations":[{"raw_affiliation_string":"Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Muhammad Awais","orcid":"https://orcid.org/0000-0002-1122-0709"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Muhammad Awais","raw_affiliation_strings":["Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K"],"raw_orcid":"https://orcid.org/0000-0002-1122-0709","affiliations":[{"raw_affiliation_string":"Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Soroush Fatemifar","orcid":"https://orcid.org/0000-0003-3460-1093"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Soroush Fatemifar","raw_affiliation_strings":["Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K"],"raw_orcid":"https://orcid.org/0000-0003-3460-1093","affiliations":[{"raw_affiliation_string":"Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":null,"display_name":"Josef Kittler","orcid":"https://orcid.org/0000-0002-8110-9205"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Josef Kittler","raw_affiliation_strings":["Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8110-9205","affiliations":[{"raw_affiliation_string":"Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":0.6122,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66146005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"45","issue":"1","first_page":"313","last_page":"328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.8515999913215637,"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/T11448","display_name":"Face recognition and analysis","score":0.8515999913215637,"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/T11094","display_name":"Face Recognition and Perception","score":0.0272000003606081,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.024000000208616257,"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/benchmark","display_name":"Benchmark (surveying)","score":0.680400013923645},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6204000115394592},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5594000220298767},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5121999979019165},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49079999327659607},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.48820000886917114},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4713999927043915},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41620001196861267}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.680400013923645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6797999739646912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6448000073432922},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6204000115394592},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5594000220298767},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5121999979019165},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49079999327659607},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4713999927043915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46230000257492065},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.367900013923645},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3301999866962433},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3158999979496002},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3156885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3156885","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:35254972","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35254972","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4770326006","display_name":null,"funder_award_id":"EP/N007743/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W1167806532","https://openalex.org/W1568307856","https://openalex.org/W1965804146","https://openalex.org/W2003447360","https://openalex.org/W2066454034","https://openalex.org/W2078807908","https://openalex.org/W2103077782","https://openalex.org/W2115394472","https://openalex.org/W2118664399","https://openalex.org/W2325939864","https://openalex.org/W2417288846","https://openalex.org/W2510725918","https://openalex.org/W2518143623","https://openalex.org/W2553156677","https://openalex.org/W2579021424","https://openalex.org/W2585518414","https://openalex.org/W2604528050","https://openalex.org/W2611767324","https://openalex.org/W2614580201","https://openalex.org/W2663800299","https://openalex.org/W2734838866","https://openalex.org/W2735418187","https://openalex.org/W2747641531","https://openalex.org/W2748140016","https://openalex.org/W2754213847","https://openalex.org/W2767315227","https://openalex.org/W2771116199","https://openalex.org/W2785230356","https://openalex.org/W2788402790","https://openalex.org/W2793495103","https://openalex.org/W2798868324","https://openalex.org/W2831800342","https://openalex.org/W2921918732","https://openalex.org/W2931027027","https://openalex.org/W2955216108","https://openalex.org/W2955863859","https://openalex.org/W2956542947","https://openalex.org/W2958622112","https://openalex.org/W2962786991","https://openalex.org/W2962851632","https://openalex.org/W2963429116","https://openalex.org/W2964084596","https://openalex.org/W2964268240","https://openalex.org/W2971130703","https://openalex.org/W2972367691","https://openalex.org/W2975221988","https://openalex.org/W2976886057","https://openalex.org/W2980096013","https://openalex.org/W2985793077","https://openalex.org/W2998166845","https://openalex.org/W2998655204","https://openalex.org/W3015317268","https://openalex.org/W3015844993","https://openalex.org/W3040291497","https://openalex.org/W3089503135","https://openalex.org/W3092466816","https://openalex.org/W3120835606","https://openalex.org/W3159915121","https://openalex.org/W3170053707","https://openalex.org/W3186135469","https://openalex.org/W3202188231","https://openalex.org/W4200262021","https://openalex.org/W4302395530","https://openalex.org/W6603271061","https://openalex.org/W6615672858","https://openalex.org/W6638214083","https://openalex.org/W6678960063","https://openalex.org/W6682962330","https://openalex.org/W6684191040","https://openalex.org/W6729109823","https://openalex.org/W6729809565","https://openalex.org/W6741832134","https://openalex.org/W6743006830","https://openalex.org/W6749061179","https://openalex.org/W6751882866","https://openalex.org/W6752398176","https://openalex.org/W6768395131","https://openalex.org/W6773566789","https://openalex.org/W6779561279","https://openalex.org/W6791083757","https://openalex.org/W6796584642"],"related_works":[],"abstract_inverted_index":{"We":[0,51,161],"consider":[1],"a":[2,20,88,104],"framework":[3],"for":[4,108,158],"taking":[5],"into":[6,57],"consideration":[7],"the":[8,16,45,48,71,80,125,129,144,147,152,155,171,189,203,206],"relative":[9],"importance":[10],"(ordinality)":[11],"of":[12,18,44,91,146,154,173,205],"object":[13],"labels":[14,46],"in":[15,40,78,94,132],"process":[17],"learning":[19,59,117,135,182],"label":[21],"predictor":[22],"function.":[23],"The":[24,195],"commonly":[25],"used":[26],"loss":[27,106,156],"functions":[28],"are":[29],"not":[30],"well":[31],"matched":[32],"to":[33,53,69,122,141,180],"this":[34,99],"problem,":[35],"as":[36,87],"they":[37],"exhibit":[38],"deficiencies":[39],"capturing":[41],"natural":[42],"correlations":[43,56],"and":[47,128,150,169,191],"corresponding":[49],"data.":[50],"propose":[52],"incorporate":[54],"such":[55],"our":[58,164,174],"algorithm":[60],"using":[61],"an":[62,133],"optimal":[63,81],"transport":[64,82],"formulation.":[65,96],"Our":[66],"approach":[67,165],"is":[68,75,119],"learn":[70],"ground":[72,126,148],"metric,":[73,149],"which":[74],"partly":[76],"involved":[77],"forming":[79],"distance,":[83],"by":[84,166,177],"leveraging":[85],"ordinality":[86],"general":[89],"form":[90],"side":[92],"information":[93],"its":[95],"Based":[97],"on":[98,198],"idea,":[100],"we":[101],"then":[102,120],"develop":[103],"novel":[105],"function":[107,157],"training":[109],"deep":[110,130],"neural":[111],"networks.":[112],"A":[113],"highly":[114],"efficient":[115],"alternating":[116],"method":[118],"devised":[121],"alternatively":[123],"optimise":[124],"metric":[127],"model":[131],"end-to-end":[134],"manner.":[136],"This":[137],"scheme":[138,176],"allows":[139],"us":[140],"adaptively":[142],"adjust":[143],"shape":[145,153],"consequently":[151],"each":[159],"application.":[160],"back":[162],"up":[163],"theoretical":[167],"analysis":[168],"verify":[170],"performance":[172],"proposed":[175,207],"applying":[178],"it":[179],"two":[181],"tasks,":[183],"i.e.":[184],"chronological":[185],"age":[186],"estimation":[187],"from":[188],"face":[190],"image":[192],"aesthetic":[193],"assessment.":[194],"numerical":[196],"results":[197],"several":[199],"benchmark":[200],"datasets":[201],"demonstrate":[202],"superiority":[204],"algorithm.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-04-03T00:00:00"}