{"id":"https://openalex.org/W2294501260","doi":"https://doi.org/10.1109/icip.2015.7351113","title":"Novel general KNN classifier and general nearest mean classifier for visual classification","display_name":"Novel general KNN classifier and general nearest mean classifier for visual classification","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2294501260","doi":"https://doi.org/10.1109/icip.2015.7351113","mag":"2294501260"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","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/A5019919993","display_name":"Qingfeng Liu","orcid":"https://orcid.org/0000-0003-1313-9418"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qingfeng Liu","raw_affiliation_strings":["Department of Computer Science, New Jersey Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Jersey Institute of Technology","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091705235","display_name":"Ajit Puthenputhussery","orcid":"https://orcid.org/0000-0001-7141-1534"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ajit Puthenputhussery","raw_affiliation_strings":["Department of Computer Science, New Jersey Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Jersey Institute of Technology","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100454866","display_name":"Chengjun Liu","orcid":"https://orcid.org/0000-0002-2036-0770"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chengjun Liu","raw_affiliation_strings":["Department of Computer Science, New Jersey Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Jersey Institute of Technology","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019919993"],"corresponding_institution_ids":["https://openalex.org/I118118575"],"apc_list":null,"apc_paid":null,"fwci":0.5523,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76131453,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1810","last_page":"1814"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9987000226974487,"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":0.9975000023841858,"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/classifier","display_name":"Classifier (UML)","score":0.774833083152771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7362385988235474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6475810408592224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6366534233093262},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5925759077072144},{"id":"https://openalex.org/keywords/nearest-neighbour","display_name":"Nearest neighbour","score":0.49460241198539734},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4706037938594818},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06621930003166199}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.774833083152771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7362385988235474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6475810408592224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6366534233093262},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5925759077072144},{"id":"https://openalex.org/C2983946233","wikidata":"https://www.wikidata.org/wiki/Q4088109","display_name":"Nearest neighbour","level":2,"score":0.49460241198539734},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4706037938594818},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06621930003166199}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7351113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1576445103","https://openalex.org/W1849277567","https://openalex.org/W1904464160","https://openalex.org/W1963932623","https://openalex.org/W1966385142","https://openalex.org/W1982405594","https://openalex.org/W2027805700","https://openalex.org/W2027922120","https://openalex.org/W2033832873","https://openalex.org/W2040895929","https://openalex.org/W2052575990","https://openalex.org/W2062118960","https://openalex.org/W2065581761","https://openalex.org/W2099528205","https://openalex.org/W2100556411","https://openalex.org/W2107698128","https://openalex.org/W2125874614","https://openalex.org/W2129812935","https://openalex.org/W2135346934","https://openalex.org/W2139468722","https://openalex.org/W2152161678","https://openalex.org/W2157785665","https://openalex.org/W2162915993","https://openalex.org/W2166049352","https://openalex.org/W2169177311","https://openalex.org/W2963173190","https://openalex.org/W3148981562","https://openalex.org/W6634343353","https://openalex.org/W6639204139","https://openalex.org/W6648737282","https://openalex.org/W6684872329"],"related_works":["https://openalex.org/W2147397890","https://openalex.org/W2166213322","https://openalex.org/W2622145841","https://openalex.org/W1591806955","https://openalex.org/W2005234362","https://openalex.org/W2062957446","https://openalex.org/W4206315490","https://openalex.org/W1997235926","https://openalex.org/W2462298708","https://openalex.org/W2291489469"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,12,33,59],"novel":[4,13],"general":[5,14],"k":[6],"nearest":[7,15],"neighbour":[8],"classifier":[9,17],"(GKNNc)":[10],"and":[11,30,45,53,74,89],"mean":[16],"(GNMc)":[18],"for":[19,51,71],"visual":[20],"classification.":[21],"Instead":[22],"of":[23,47,98],"treating":[24],"the":[25,43,48,68,85,90,96,99],"data":[26,81],"equally,":[27],"both":[28,72],"GKNNc":[29,52,73],"GNMc":[31,54],"assign":[32],"weight":[34,49,69],"coefficient":[35],"to":[36,66],"each":[37],"data.":[38],"To":[39],"achieve":[40],"good":[41],"performance,":[42],"conditions":[44],"properties":[46],"coefficients":[50,70],"are":[55],"further":[56],"analysed.":[57],"Then":[58],"sparse":[60],"representation":[61],"based":[62],"method":[63],"is":[64],"proposed":[65,100],"derive":[67],"GNMc.":[75],"Experimental":[76],"results":[77],"on":[78],"several":[79],"representative":[80],"sets,":[82],"such":[83],"as":[84],"Caltech":[86],"101":[87],"dataset":[88,94],"MIT-67":[91],"indoor":[92],"scenes":[93],"demonstrate":[95],"feasibility":[97],"methods.":[101]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
