{"id":"https://openalex.org/W2942081340","doi":"https://doi.org/10.1109/access.2019.2912932","title":"Graph-Regularized Discriminative Analysis-Synthesis Dictionary Pair Learning for Image Classification","display_name":"Graph-Regularized Discriminative Analysis-Synthesis Dictionary Pair Learning for Image Classification","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2942081340","doi":"https://doi.org/10.1109/access.2019.2912932","mag":"2942081340"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2912932","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2912932","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2019.2912932","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068232881","display_name":"Heyou Chang","orcid":"https://orcid.org/0000-0002-9536-4311"},"institutions":[{"id":"https://openalex.org/I4210128418","display_name":"Nanjing Xiaozhuang University","ror":"https://ror.org/03fnv7n42","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128418"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyou Chang","raw_affiliation_strings":["Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9536-4311","affiliations":[{"raw_affiliation_string":"Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University, Nanjing, China","institution_ids":["https://openalex.org/I4210128418"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083564415","display_name":"Hui Tang","orcid":"https://orcid.org/0000-0001-8448-6623"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Tang","raw_affiliation_strings":["Laboratory of Image Science and Technology, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Image Science and Technology, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089345835","display_name":"Fanlong Zhang","orcid":"https://orcid.org/0000-0001-8865-9683"},"institutions":[{"id":"https://openalex.org/I206777745","display_name":"Nanjing Audit University","ror":"https://ror.org/04zj2bd87","country_code":"CN","type":"education","lineage":["https://openalex.org/I206777745"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanlong Zhang","raw_affiliation_strings":["School of Technology, Nanjing Audit University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Technology, Nanjing Audit University, Nanjing, China","institution_ids":["https://openalex.org/I206777745"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350437","display_name":"Yang Chen","orcid":"https://orcid.org/0000-0002-5660-6349"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Chen","raw_affiliation_strings":["Laboratory of Image Science and Technology, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5660-6349","affiliations":[{"raw_affiliation_string":"Laboratory of Image Science and Technology, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085132445","display_name":"Hao Zheng","orcid":"https://orcid.org/0000-0003-0829-9660"},"institutions":[{"id":"https://openalex.org/I4210128418","display_name":"Nanjing Xiaozhuang University","ror":"https://ror.org/03fnv7n42","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128418"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zheng","raw_affiliation_strings":["Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-0829-9660","affiliations":[{"raw_affiliation_string":"Key Laboratory of Trusted Cloud Computing and Big Data Analysis, Nanjing Xiaozhuang University, Nanjing, China","institution_ids":["https://openalex.org/I4210128418"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.794,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.76272068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"55398","last_page":"55406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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":0.9976999759674072,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/discriminative-model","display_name":"Discriminative model","score":0.9243353605270386},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7669438719749451},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6856683492660522},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6845813989639282},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5978660583496094},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.5773822665214539},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.5513191819190979},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5065721273422241},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5054290294647217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4146898090839386},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.3625856041908264},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2858208417892456},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14258211851119995}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9243353605270386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7669438719749451},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6856683492660522},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6845813989639282},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5978660583496094},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.5773822665214539},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5513191819190979},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5065721273422241},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5054290294647217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4146898090839386},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.3625856041908264},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2858208417892456},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14258211851119995}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2912932","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2912932","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:93fcef05b8f04538985ab3936a6a4e47","is_oa":false,"landing_page_url":"https://doaj.org/article/93fcef05b8f04538985ab3936a6a4e47","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 55398-55406 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2912932","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2912932","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.75}],"awards":[{"id":"https://openalex.org/G1680049189","display_name":null,"funder_award_id":"18KJB520029","funder_id":"https://openalex.org/F4320335440","funder_display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China"},{"id":"https://openalex.org/G2071029159","display_name":"\u7528\u4e8e\u80ba\u764c\u7cbe\u51c6\u653e\u7597\u7684\u9ad8\u5206\u8fa8\u79fb\u52a8\u6761\u5e26CT\u5f71\u50cf\u5f15\u5bfc\u5173\u952e\u6280\u672f\u57fa\u7840\u7814\u7a76","funder_award_id":"81530060","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G351804187","display_name":null,"funder_award_id":"61806098","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3931407312","display_name":null,"funder_award_id":"2017NXY49","funder_id":"https://openalex.org/F4320325416","funder_display_name":"Nanjing Xiaozhuang University"},{"id":"https://openalex.org/G811154747","display_name":null,"funder_award_id":"61603192","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8261766890","display_name":null,"funder_award_id":"81471752","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325416","display_name":"Nanjing Xiaozhuang University","ror":"https://ror.org/03fnv7n42"},{"id":"https://openalex.org/F4320335440","display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W129703402","https://openalex.org/W1576445103","https://openalex.org/W1963932623","https://openalex.org/W1973723602","https://openalex.org/W1982405594","https://openalex.org/W1994281301","https://openalex.org/W2011464887","https://openalex.org/W2016584925","https://openalex.org/W2046779692","https://openalex.org/W2053186076","https://openalex.org/W2097308346","https://openalex.org/W2108119513","https://openalex.org/W2117553576","https://openalex.org/W2120552947","https://openalex.org/W2124386111","https://openalex.org/W2140245639","https://openalex.org/W2152171106","https://openalex.org/W2160547390","https://openalex.org/W2162915993","https://openalex.org/W2166049352","https://openalex.org/W2166371785","https://openalex.org/W2293272929","https://openalex.org/W2299333792","https://openalex.org/W2343962831","https://openalex.org/W2545426943","https://openalex.org/W2560042709","https://openalex.org/W2564013914","https://openalex.org/W2621368543","https://openalex.org/W2624147939","https://openalex.org/W2766610223","https://openalex.org/W2780930362","https://openalex.org/W2782796222","https://openalex.org/W2890764008","https://openalex.org/W2903817566","https://openalex.org/W2905902135","https://openalex.org/W2914004410","https://openalex.org/W2915902994","https://openalex.org/W2953139536","https://openalex.org/W2962744053","https://openalex.org/W2963418726","https://openalex.org/W3099751318","https://openalex.org/W3118608800","https://openalex.org/W4232730838","https://openalex.org/W6605295242","https://openalex.org/W6634343353","https://openalex.org/W6674642818","https://openalex.org/W6676321539","https://openalex.org/W6678757208","https://openalex.org/W6684213969","https://openalex.org/W6730694978","https://openalex.org/W6757972424","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2509955295","https://openalex.org/W1778286912","https://openalex.org/W1987225540","https://openalex.org/W2152958724","https://openalex.org/W2116933539","https://openalex.org/W2099321050","https://openalex.org/W4245251483","https://openalex.org/W2008821896","https://openalex.org/W2034957211","https://openalex.org/W1992008660"],"abstract_inverted_index":{"Analysis-synthesis":[0],"dictionary":[1,31,51,67,97,131],"pair":[2,32,52,68],"learning,":[3],"which":[4,56],"can":[5,79],"provide":[6],"a":[7,44,57,61,147],"comprehensive":[8],"view":[9],"of":[10,47,73,85],"data":[11],"representation,":[12],"has":[13,24],"been":[14,25],"applied":[15],"in":[16,27,55,126],"various":[17],"computer":[18],"vision":[19],"tasks.":[20],"Although":[21],"good":[22],"performance":[23,145],"reported":[26],"image":[28,35,120],"denoising,":[29],"discriminative":[30,49,62],"learning":[33,53,132],"for":[34],"classification":[36],"remains":[37],"unsolved.":[38],"In":[39,99],"this":[40,100],"paper,":[41,101],"we":[42],"propose":[43],"novel":[45],"model":[46,142],"graph-regularized":[48,58],"analysis-synthesis":[50],"(GDASDL),":[54],"term":[59,63],"and":[60,122,134],"are":[64],"incorporated":[65],"into":[66],"learning.":[69],"By":[70],"taking":[71],"advantage":[72],"graph":[74],"constraints,":[75],"the":[76,81,86,110,129,135,140],"proposed":[77,111,141],"GDASDL":[78],"preserve":[80],"local":[82],"geometry":[83],"structure":[84],"data.":[87],"Global":[88],"information":[89,95],"is":[90,105],"introduced":[91],"by":[92],"associating":[93],"label":[94],"with":[96,128],"atoms.":[98],"an":[102],"iteration":[103],"algorithm":[104],"presented":[106],"to":[107],"efficiently":[108],"solve":[109],"GDASDL.":[112],"We":[113],"extensively":[114],"conduct":[115],"experiments":[116],"on":[117],"three":[118],"public":[119],"datasets":[121],"one":[123],"face":[124],"dataset":[125],"comparison":[127],"existing":[130],"approaches,":[133],"experimental":[136],"results":[137],"show":[138],"that":[139],"achieves":[143],"superior":[144],"using":[146],"simple":[148],"linear":[149],"classifier.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}