{"id":"https://openalex.org/W1989799483","doi":"https://doi.org/10.1109/icme.2013.6607556","title":"Neighborhood reversibility verifying for image search","display_name":"Neighborhood reversibility verifying for image search","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1989799483","doi":"https://doi.org/10.1109/icme.2013.6607556","mag":"1989799483"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2013.6607556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2013.6607556","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 Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5051044069","display_name":"Zhong Zheng","orcid":"https://orcid.org/0000-0002-1741-0554"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Zheng","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, Beijing, CN","[Institute of Information Science, Beijing JiaoTong University, Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"[Institute of Information Science, Beijing JiaoTong University, Beijing, China]","institution_ids":["https://openalex.org/I21193070"]}]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, Beijing, CN","[Institute of Information Science, Beijing JiaoTong University, Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"[Institute of Information Science, Beijing JiaoTong University, Beijing, China]","institution_ids":["https://openalex.org/I21193070"]}]},{"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shikui Wei","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, Beijing, CN","[Institute of Information Science, Beijing JiaoTong University, Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"[Institute of Information Science, Beijing JiaoTong University, Beijing, China]","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101867605","display_name":"Zhenfeng Zhu","orcid":"https://orcid.org/0000-0001-7315-3276"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfeng Zhu","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, Beijing, CN","[Institute of Information Science, Beijing JiaoTong University, Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"[Institute of Information Science, Beijing JiaoTong University, Beijing, China]","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"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":0.9998999834060669,"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":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.998199999332428,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/robustness","display_name":"Robustness (evolution)","score":0.7755111455917358},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6491740942001343},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6056655645370483},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5114976167678833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49570000171661377},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4363975524902344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43372732400894165},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3712775707244873},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36755067110061646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2629207670688629}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7755111455917358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6491740942001343},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6056655645370483},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5114976167678833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49570000171661377},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4363975524902344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43372732400894165},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3712775707244873},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36755067110061646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2629207670688629},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2013.6607556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2013.6607556","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 Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1544060217","https://openalex.org/W1556531089","https://openalex.org/W1843927653","https://openalex.org/W1979931042","https://openalex.org/W2023991840","https://openalex.org/W2100398441","https://openalex.org/W2112429522","https://openalex.org/W2113276649","https://openalex.org/W2128017662","https://openalex.org/W2131846894","https://openalex.org/W2141362318","https://openalex.org/W2148809531","https://openalex.org/W2149991777","https://openalex.org/W2151103935","https://openalex.org/W2156365280","https://openalex.org/W6632673259","https://openalex.org/W6638747085"],"related_works":["https://openalex.org/W2152992791","https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W4281727072","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W2377538627","https://openalex.org/W2107220315","https://openalex.org/W1589637664"],"abstract_inverted_index":{"The":[0,111],"neighborhood":[1,16,38,53,91,107],"structure":[2],"can":[3],"significantly":[4],"impact":[5],"the":[6,13,19,33,49,59,62,75,81,88,117,122,135],"effectiveness":[7],"of":[8,15,36,52,77,90,106],"image":[9,20,63,94,123,140],"search,":[10],"and":[11,28,97,126],"fulfilling":[12],"reversibility":[14,54,76,108],"may":[17],"improve":[18],"search":[21,64,95,124],"quality.":[22],"This":[23],"paper":[24],"proposes":[25],"an":[26,99],"effective":[27],"efficient":[29],"scheme":[30,102,119],"for":[31,103,138],"reconstructing":[32],"symmetry":[34],"relationship":[35,79],"k-nearest":[37],"(KNN).":[39],"In":[40,83],"particular,":[41],"we":[42,85],"design":[43],"a":[44,128],"verifying":[45],"function":[46],"to":[47,70,134],"learn":[48],"prior":[50,60],"knowledge":[51],"among":[55],"images.":[56],"By":[57],"exploiting":[58],"knowledge,":[61],"system":[65],"will":[66],"give":[67,127],"higher":[68],"rank":[69],"those":[71],"images":[72],"that":[73,116],"satisfy":[74],"KNN":[78],"with":[80],"query.":[82],"addition,":[84],"systematically":[86],"investigate":[87],"sensitivity":[89],"size":[92],"on":[93],"quality":[96,125],"propose":[98],"adaptive":[100],"selection":[101],"improving":[104],"robustness":[105],"learning":[109],"methods.":[110],"extensive":[112],"experimental":[113],"results":[114],"show":[115],"proposed":[118],"remarkably":[120],"improves":[121],"comparable":[129],"but":[130],"more":[131],"stable":[132],"performance":[133],"state-of-the-art":[136],"method":[137],"various":[139],"datasets.":[141]},"counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}