{"id":"https://openalex.org/W2090892265","doi":"https://doi.org/10.1109/icip.2013.6738670","title":"Representative reference-set and betweenness centrality for scene image categorization","display_name":"Representative reference-set and betweenness centrality for scene image categorization","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2090892265","doi":"https://doi.org/10.1109/icip.2013.6738670","mag":"2090892265"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","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/A5100426173","display_name":"Qun Li","orcid":"https://orcid.org/0000-0002-8034-6030"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qun Li","raw_affiliation_strings":["Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100763094","display_name":"Zhen Qin","orcid":"https://orcid.org/0000-0001-6739-134X"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhen Qin","raw_affiliation_strings":["University of California, Riverside, CA, USA","University of California, RIverside, Riverside, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]},{"raw_affiliation_string":"University of California, RIverside, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102081059","display_name":"Lunshao Chai","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lunshao Chai","raw_affiliation_strings":["Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100626771","display_name":"Honggang Zhang","orcid":"https://orcid.org/0000-0001-8287-6783"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honggang Zhang","raw_affiliation_strings":["Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445470","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0001-9045-1339"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Laboratory, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071522801","display_name":"Bir Bhanu","orcid":"https://orcid.org/0000-0001-8971-6416"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bir Bhanu","raw_affiliation_strings":["University of California, Riverside, CA, USA","University of California, RIverside, Riverside, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]},{"raw_affiliation_string":"University of California, RIverside, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2763,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62657473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3254","last_page":"3258"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9984999895095825,"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/T10824","display_name":"Image Retrieval and Classification 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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7099916934967041},{"id":"https://openalex.org/keywords/betweenness-centrality","display_name":"Betweenness centrality","score":0.6735939383506775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6693357229232788},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6490654945373535},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6195467710494995},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.575186550617218},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5120206475257874},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.46853676438331604},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.44686007499694824},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4372836947441101},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4253886640071869},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42458346486091614},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.41129952669143677},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.35928183794021606},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33767327666282654},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.170741468667984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099916934967041},{"id":"https://openalex.org/C117045392","wikidata":"https://www.wikidata.org/wiki/Q4899215","display_name":"Betweenness centrality","level":3,"score":0.6735939383506775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6693357229232788},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6490654945373535},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6195467710494995},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.575186550617218},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5120206475257874},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.46853676438331604},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.44686007499694824},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4372836947441101},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4253886640071869},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42458346486091614},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.41129952669143677},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.35928183794021606},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33767327666282654},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.170741468667984},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2013.6738670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.657.2110","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.657.2110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vislab.ucr.edu/PUBLICATIONS/pubs/Journal+and+Conference+Papers/after10-1-1997/Conference/2013/Representative+reference-set+and+betweenness+centrality+for+scene+image+categorization13.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6700000166893005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1576445103","https://openalex.org/W2027805700","https://openalex.org/W2027922120","https://openalex.org/W2056077615","https://openalex.org/W2084716923","https://openalex.org/W2097018403","https://openalex.org/W2107034620","https://openalex.org/W2122162561","https://openalex.org/W2134563198","https://openalex.org/W2145406111","https://openalex.org/W2162915993","https://openalex.org/W2166049352","https://openalex.org/W2186094539","https://openalex.org/W4232730838","https://openalex.org/W6634343353","https://openalex.org/W6674642818","https://openalex.org/W6679809621"],"related_works":["https://openalex.org/W1973509935","https://openalex.org/W4389076551","https://openalex.org/W2107855069","https://openalex.org/W2611574733","https://openalex.org/W2241641394","https://openalex.org/W2097992793","https://openalex.org/W2140653560","https://openalex.org/W2348831795","https://openalex.org/W4312461432","https://openalex.org/W2514739320"],"abstract_inverted_index":{"Reference-based":[0],"image":[1,9,83,91,124],"classification":[2,59,84],"approach":[3],"introduces":[4],"a":[5,52,77,98,111],"reference-set":[6,55,105],"for":[7],"both":[8],"representation":[10],"and":[11,22,32,125],"dictionary":[12],"learning.":[13],"It":[14],"significantly":[15],"reduces":[16],"the":[17,67,72,82,103,118,122,126],"dimensionality":[18],"of":[19,102],"represented":[20],"images":[21,31],"shows":[23],"outstanding":[24],"performance":[25,138],"even":[26],"with":[27,44],"randomly":[28],"selected":[29],"reference":[30],"simple":[33],"distance":[34,114],"measure.":[35],"In":[36],"this":[37,62],"paper,":[38],"we":[39,49,64,86],"improve":[40],"upon":[41],"existing":[42,140],"work":[43],"two":[45],"major":[46],"contributions.":[47],"First,":[48],"show":[50],"that":[51,116,132],"more":[53,112],"representative":[54,104],"contributes":[56],"to":[57,75,88,110],"better":[58,137],"accuracy.":[60],"To":[61],"end,":[63],"carefully":[65],"adapt":[66],"K-means":[68],"clustering":[69],"algorithm":[70],"in":[71,81,97,106],"feature":[73],"space":[74],"select":[76],"distinguished":[78],"reference-set.":[79,127],"Second,":[80],"process,":[85],"propose":[87],"represent":[89],"each":[90,107],"by":[92],"measuring":[93],"its":[94],"betweenness":[95],"centrality":[96],"social":[99],"network":[100],"composed":[101],"class,":[108],"leading":[109],"coherent":[113],"measure":[115],"considers":[117],"overall":[119],"connectivity":[120],"between":[121],"probe":[123],"Extensive":[128],"experiment":[129],"results":[130],"demonstrate":[131],"our":[133],"proposed":[134],"scheme":[135],"achieves":[136],"than":[139],"methods.":[141]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}