{"id":"https://openalex.org/W2104376766","doi":"https://doi.org/10.1145/2438653.2438669","title":"Learning image-to-class distance metric for image classification","display_name":"Learning image-to-class distance metric for image classification","publication_year":2013,"publication_date":"2013-03-01","ids":{"openalex":"https://openalex.org/W2104376766","doi":"https://doi.org/10.1145/2438653.2438669","mag":"2104376766"},"language":"en","primary_location":{"id":"doi:10.1145/2438653.2438669","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2438653.2438669","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-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/A5077410212","display_name":"Zhengxiang Wang","orcid":"https://orcid.org/0000-0003-0274-4639"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhengxiang Wang","raw_affiliation_strings":["Nanyang Technological University, Singapore","Nanyang Technological University (Singapore)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University (Singapore)","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102837904","display_name":"Yiqun Hu","orcid":"https://orcid.org/0000-0001-9157-7865"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yiqun Hu","raw_affiliation_strings":["The University of Western Australia, Crawley, WA, Australia",", The University of Western Australia, Crawley, WA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Western Australia, Crawley, WA, Australia","institution_ids":["https://openalex.org/I177877127"]},{"raw_affiliation_string":", The University of Western Australia, Crawley, WA, Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110091686","display_name":"Liang-Tien Chia","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Liang-Tien Chia","raw_affiliation_strings":["Nanyang Technological University, Singapore","Nanyang Technological University (Singapore)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University (Singapore)","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.816,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.77587789,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"4","issue":"2","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9886999726295471,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9886999726295471,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.8785122632980347},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.6708195209503174},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6573386788368225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6078307032585144},{"id":"https://openalex.org/keywords/distance-matrix","display_name":"Distance matrix","score":0.6054712533950806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5965125560760498},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.5759567618370056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5519117116928101},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5038303732872009},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.44856756925582886},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35280299186706543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2655959725379944},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2562125027179718}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.8785122632980347},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.6708195209503174},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6573386788368225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6078307032585144},{"id":"https://openalex.org/C111208986","wikidata":"https://www.wikidata.org/wiki/Q901698","display_name":"Distance matrix","level":2,"score":0.6054712533950806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5965125560760498},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.5759567618370056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5519117116928101},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5038303732872009},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.44856756925582886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35280299186706543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2655959725379944},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2562125027179718},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2438653.2438669","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2438653.2438669","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/6390e98c-e3ee-4269-9360-b50b7e1e561b","is_oa":false,"landing_page_url":"https://research-repository.uwa.edu.au/en/publications/6390e98c-e3ee-4269-9360-b50b7e1e561b","pdf_url":null,"source":{"id":"https://openalex.org/S4306402523","display_name":"UWA Profiles and Research Repository (University of Western Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wang , Z , Hu , Y &amp; Chia , L 2013 , ' Learning image-to-class distance metric for image classification ' , ACM Transactions on Intelligent Systems and Technology , vol. 4 , no. 2 , pp. 22pp . https://doi.org/10.1145/2438653.2438659","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1488783102","https://openalex.org/W1566135517","https://openalex.org/W1576445103","https://openalex.org/W1576767704","https://openalex.org/W1733921475","https://openalex.org/W2001141328","https://openalex.org/W2027922120","https://openalex.org/W2053186076","https://openalex.org/W2066941820","https://openalex.org/W2097018403","https://openalex.org/W2101098151","https://openalex.org/W2103897297","https://openalex.org/W2104978738","https://openalex.org/W2106053110","https://openalex.org/W2107034620","https://openalex.org/W2108588392","https://openalex.org/W2111125131","https://openalex.org/W2119605622","https://openalex.org/W2125574651","https://openalex.org/W2126338813","https://openalex.org/W2127921742","https://openalex.org/W2127964696","https://openalex.org/W2129156852","https://openalex.org/W2134982367","https://openalex.org/W2137736727","https://openalex.org/W2139618600","https://openalex.org/W2144935315","https://openalex.org/W2147486662","https://openalex.org/W2151103935","https://openalex.org/W2152010828","https://openalex.org/W2155904486","https://openalex.org/W2162915993","https://openalex.org/W2166742463","https://openalex.org/W2169495281","https://openalex.org/W2186222003","https://openalex.org/W2532478580","https://openalex.org/W2912168530","https://openalex.org/W2999575747","https://openalex.org/W4233164864","https://openalex.org/W4245550249","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W2169159254","https://openalex.org/W1605858995","https://openalex.org/W149647761","https://openalex.org/W2434201124","https://openalex.org/W2183624858","https://openalex.org/W1973243276","https://openalex.org/W2908357282","https://openalex.org/W4310043907","https://openalex.org/W1969234006","https://openalex.org/W4390673421"],"abstract_inverted_index":{"Image-To-Class":[0],"(I2C)":[1],"distance":[2,6,24,28,41,54,64,77,111,177,185,190],"is":[3,78,137,227],"a":[4,53,71,101,130,162],"novel":[5],"used":[7],"for":[8,25,89,165,216],"image":[9,45,115,197],"classification":[10,46],"and":[11,147,199],"has":[12],"successfully":[13],"handled":[14],"datasets":[15],"with":[16,85,105],"large":[17,72,131],"intra-class":[18],"variances.":[19],"However,":[20],"it":[21],"uses":[22],"Euclidean":[23,183],"measuring":[26],"the":[27,39,60,86,106,109,124,158,181,206,212,231,238],"between":[29],"local":[30],"features":[31],"in":[32,43,70,170,194,222],"different":[33,81],"classes,":[34],"which":[35,235],"may":[36],"not":[37],"be":[38,121],"optimal":[40],"metric":[42,55,88,191,213],"real":[44],"problems.":[47],"In":[48],"this":[49,142],"article,":[50],"we":[51,152],"propose":[52],"learning":[56,66,192,214],"method":[57,136,159,226],"to":[58,80,116,126,139,149,156,160,229],"improve":[59],"performance":[61,207],"of":[62],"I2C":[63,76,110,176,184],"by":[65,83,99,129],"per-class":[67,94],"Mahalanobis":[68,175],"metrics":[69,95],"margin":[73],"framework.":[74],"Our":[75],"adaptive":[79],"classes":[82,128,242],"combining":[84],"learned":[87,97,174],"each":[90,113,166],"class.":[91,167],"These":[92],"multiple":[93],"are":[96],"simultaneously":[98],"forming":[100],"convex":[102],"optimization":[103,143],"problem":[104],"constraints":[107],"that":[108,172,224],"from":[112],"training":[114,245],"its":[117],"belonging":[118],"class":[119,232],"should":[120],"less":[122],"than":[123],"distances":[125],"other":[127,189],"margin.":[132],"A":[133],"subgradient":[134],"descent":[135],"applied":[138],"efficiently":[140],"solve":[141],"problem.":[144],"For":[145],"efficiency":[146],"scalability":[148],"large-scale":[150,217],"problems,":[151],"also":[153,220],"show":[154,169,221],"how":[155],"simplify":[157],"learn":[161],"diagonal":[163,202],"matrix":[164],"We":[168,219],"experiments":[171],"our":[173,200,225],"can":[178,204],"significantly":[179,209],"outperform":[180],"original":[182],"as":[186,188],"well":[187],"methods":[193,240],"several":[195],"prevalent":[196],"datasets,":[198],"simplified":[201],"matrices":[203],"preserve":[205],"but":[208],"speed":[210],"up":[211],"procedure":[215],"datasets.":[218],"experiment":[223],"able":[228],"correct":[230],"imbalance":[233],"problem,":[234],"usually":[236],"leads":[237],"NN-based":[239],"toward":[241],"containing":[243],"more":[244],"images.":[246]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
