{"id":"https://openalex.org/W2517665472","doi":"https://doi.org/10.1109/icme.2016.7552945","title":"Improving the similarity estimation via score distribution","display_name":"Improving the similarity estimation via score distribution","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2517665472","doi":"https://doi.org/10.1109/icme.2016.7552945","mag":"2517665472"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2016.7552945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2016.7552945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-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/A5080547175","display_name":"Lixin Liao","orcid":"https://orcid.org/0009-0004-6712-5729"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]},{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lixin Liao","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China","School of Information Science and Engineering, Yanshan University, shkwei, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Information Science and Engineering, Yanshan University, shkwei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006854141","display_name":"Shikui Wei","orcid":"https://orcid.org/0000-0003-3803-9763"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]},{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shikui Wei","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China","School of Information Science and Engineering, Yanshan University, shkwei, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Information Science and Engineering, Yanshan University, shkwei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362745","display_name":"Yao Zhao","orcid":"https://orcid.org/0000-0002-8581-9554"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]},{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China","School of Information Science and Engineering, Yanshan University, shkwei, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Information Science and Engineering, Yanshan University, shkwei, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080706260","display_name":"Guanghua Gu","orcid":"https://orcid.org/0000-0002-9532-8273"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]},{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghua Gu","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China","School of Information Science and Engineering, Yanshan University, shkwei, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Information Science and Engineering, Yanshan University, shkwei, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5080547175"],"corresponding_institution_ids":["https://openalex.org/I21193070","https://openalex.org/I39333907"],"apc_list":null,"apc_paid":null,"fwci":0.835,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80636716,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"30","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9984999895095825,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9872999787330627,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7982645034790039},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.663079023361206},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.6515085697174072},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6306387186050415},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5929414629936218},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5911824107170105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5568305253982544},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5461077690124512},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4581969380378723},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.44419461488723755},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4334731996059418},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41014406085014343},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3339861035346985}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7982645034790039},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.663079023361206},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.6515085697174072},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6306387186050415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5929414629936218},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5911824107170105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5568305253982544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5461077690124512},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4581969380378723},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.44419461488723755},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4334731996059418},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41014406085014343},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3339861035346985},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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":1,"locations":[{"id":"doi:10.1109/icme.2016.7552945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2016.7552945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1123427201","https://openalex.org/W1556531089","https://openalex.org/W1566135517","https://openalex.org/W1820015093","https://openalex.org/W1935207225","https://openalex.org/W1972195523","https://openalex.org/W1976879861","https://openalex.org/W1989799483","https://openalex.org/W2012592962","https://openalex.org/W2101098151","https://openalex.org/W2128017662","https://openalex.org/W2130556178","https://openalex.org/W2131846894","https://openalex.org/W2136885397","https://openalex.org/W2141362318","https://openalex.org/W2142126424","https://openalex.org/W2142385580","https://openalex.org/W2146983301","https://openalex.org/W2147238549","https://openalex.org/W2151103935","https://openalex.org/W2154952031","https://openalex.org/W2155893237","https://openalex.org/W2156365280","https://openalex.org/W2157364932","https://openalex.org/W2163605009","https://openalex.org/W2799061466","https://openalex.org/W4247915583","https://openalex.org/W4302161581","https://openalex.org/W6627111012","https://openalex.org/W6647508389","https://openalex.org/W6674896937","https://openalex.org/W6675751002","https://openalex.org/W6681667653","https://openalex.org/W6682717316","https://openalex.org/W6684191040","https://openalex.org/W7014191107"],"related_works":["https://openalex.org/W2319693127","https://openalex.org/W308539617","https://openalex.org/W1983228818","https://openalex.org/W2163064108","https://openalex.org/W2072263576","https://openalex.org/W2474567666","https://openalex.org/W2990913351","https://openalex.org/W2767257176","https://openalex.org/W2915154372","https://openalex.org/W4399930146"],"abstract_inverted_index":{"Generally":[0],"distance-based":[1],"similarity":[2,33,41,56,79,112],"estimation":[3,34,113],"between":[4,84],"two":[5],"images":[6,62],"is":[7,46],"not":[8],"always":[9],"reliable":[10],"due":[11],"to":[12,93],"the":[13,32,37,53,74,77,82,95,110,116,121],"limitations":[14],"in":[15],"both":[16],"image":[17],"understanding":[18],"techniques":[19],"and":[20,91,120,133],"distance":[21,97,118],"measure":[22,119],"methods.":[23],"This":[24],"paper":[25],"presents":[26],"a":[27,126],"novel":[28],"approach":[29,123],"for":[30,60],"improving":[31],"through":[35],"introducing":[36],"distribution":[38,72],"information":[39],"of":[40,55],"scores.":[42],"The":[43],"key":[44],"idea":[45],"based":[47],"on":[48,100,130],"an":[49,66],"underlying":[50],"assumption":[51],"that":[52,109],"distributions":[54,86],"scores":[57],"are":[58],"similar":[59],"true-relevant":[61],"when":[63],"they":[64],"query":[65],"independent":[67],"database.":[68],"By":[69],"representing":[70],"each":[71],"with":[73,104],"area":[75],"under":[76],"corresponding":[78],"score":[80],"curve,":[81],"difference":[83],"different":[85],"can":[87],"be":[88],"easily":[89],"calculated":[90],"employed":[92],"update":[94],"original":[96,117],"measure.":[98],"Experiments":[99],"three":[101],"public":[102],"datasets":[103,132],"various":[105,131],"feature":[106,134],"representations":[107],"show":[108],"enhanced":[111],"remarkably":[114],"outperforms":[115],"proposed":[122],"also":[124],"keeps":[125],"good":[127],"generalization":[128],"ability":[129],"representations.":[135]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
