{"id":"https://openalex.org/W2038014783","doi":"https://doi.org/10.1145/2499788.2499854","title":"Locality discriminative coding for image classification","display_name":"Locality discriminative coding for image classification","publication_year":2013,"publication_date":"2013-08-17","ids":{"openalex":"https://openalex.org/W2038014783","doi":"https://doi.org/10.1145/2499788.2499854","mag":"2038014783"},"language":"en","primary_location":{"id":"doi:10.1145/2499788.2499854","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2499788.2499854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service","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/A5083991825","display_name":"Xiaoshan Yang","orcid":"https://orcid.org/0000-0001-5453-9755"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoshan Yang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648981","display_name":"Tianzhu Zhang","orcid":"https://orcid.org/0000-0003-1856-9564"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianzhu Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":0.8288,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.76628247,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"52","last_page":"55"},"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":0.9995999932289124,"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":0.9995999932289124,"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":0.9876000285148621,"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":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7942931652069092},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7137005925178528},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7062796354293823},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.6925252079963684},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.6828373074531555},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6777033805847168},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.6731375455856323},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.6347085237503052},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5147309303283691},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.4906803369522095},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.47983357310295105},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.4778189957141876},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4612712860107422},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45648667216300964},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.44415271282196045},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.419309139251709},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.3487675189971924},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3341500759124756},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.2943859100341797},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2766529321670532},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17487570643424988},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06783628463745117}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7942931652069092},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7137005925178528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7062796354293823},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.6925252079963684},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.6828373074531555},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6777033805847168},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.6731375455856323},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.6347085237503052},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5147309303283691},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.4906803369522095},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.47983357310295105},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.4778189957141876},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4612712860107422},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45648667216300964},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.44415271282196045},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.419309139251709},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.3487675189971924},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3341500759124756},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.2943859100341797},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2766529321670532},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17487570643424988},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06783628463745117},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2499788.2499854","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2499788.2499854","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3002881766","display_name":null,"funder_award_id":"61272329, 61225009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4605514923","display_name":null,"funder_award_id":"4131004","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321038","display_name":"Fonds National de la Recherche Luxembourg","ror":"https://ror.org/039z13y21"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1576767704","https://openalex.org/W1625255723","https://openalex.org/W2003115311","https://openalex.org/W2027922120","https://openalex.org/W2050964073","https://openalex.org/W2097018403","https://openalex.org/W2117483887","https://openalex.org/W2118585731","https://openalex.org/W2123745357","https://openalex.org/W2131846894","https://openalex.org/W2145406111","https://openalex.org/W2147625498","https://openalex.org/W2150856297","https://openalex.org/W2155904486","https://openalex.org/W2162915993","https://openalex.org/W2166742463","https://openalex.org/W2167986384"],"related_works":["https://openalex.org/W2391617560","https://openalex.org/W4392546545","https://openalex.org/W3000274722","https://openalex.org/W1615295117","https://openalex.org/W2350926174","https://openalex.org/W2473933584","https://openalex.org/W2412408867","https://openalex.org/W2949855236","https://openalex.org/W2091283871","https://openalex.org/W4301959110"],"abstract_inverted_index":{"The":[0],"Bag-of-Words":[1],"(BOW)":[2],"based":[3,53,58,119,123],"methods":[4,32,44,117],"are":[5],"widely":[6],"used":[7],"in":[8,20],"image":[9,115],"classification.":[10],"However,":[11],"huge":[12],"number":[13],"of":[14,24,62],"visual":[15],"information":[16],"is":[17],"omitted":[18],"inevitably":[19],"the":[21,25,50,60,90],"quantization":[22],"step":[23],"BOW.":[26],"Recently,":[27],"NBNN":[28,35],"and":[29,64],"its":[30],"improved":[31],"like":[33],"Local":[34,65,91],"were":[36],"proposed":[37],"to":[38],"solve":[39],"this":[40,56],"problem.":[41],"Nevertheless,":[42],"these":[43],"do":[45],"not":[46],"perform":[47],"better":[48],"than":[49,95],"state-of-the-art":[51,114],"BOW":[52,63],"methods.":[54],"In":[55],"paper,":[57],"on":[59,102,120,124],"advantages":[61],"NBNN,":[66,121],"we":[67],"introduce":[68],"a":[69],"novel":[70],"locality":[71],"discriminative":[72],"coding":[73],"(LDC)":[74],"method.":[75],"We":[76],"convert":[77],"each":[78],"low":[79],"level":[80],"local":[81],"feature,":[82],"such":[83],"as":[84],"SIFT,":[85],"into":[86],"code":[87],"vector":[88],"using":[89],"Feature-to-Class":[92],"distance":[93],"other":[94],"by":[96],"k-means":[97],"quantization.":[98],"Extensive":[99],"experimental":[100],"results":[101],"4":[103],"challenging":[104],"benchmark":[105],"datasets":[106],"show":[107],"that":[108],"our":[109],"LDC":[110],"method":[111],"outperforms":[112],"6":[113],"classification":[116],"(3":[118],"3":[122],"BOW).":[125]},"counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}