{"id":"https://openalex.org/W2197419489","doi":"https://doi.org/10.1117/12.2204911","title":"Maximum constrained sparse coding for image representation","display_name":"Maximum constrained sparse coding for image representation","publication_year":2015,"publication_date":"2015-12-14","ids":{"openalex":"https://openalex.org/W2197419489","doi":"https://doi.org/10.1117/12.2204911","mag":"2197419489"},"language":"en","primary_location":{"id":"doi:10.1117/12.2204911","doi":"https://doi.org/10.1117/12.2204911","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2204911","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5100436609","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0001-5946-8319","observed_orcids":["https://orcid.org/0000-0001-5946-8319"]},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["Beihang Univ. (China)","Beijing Key Lab. of Digital Media (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang Univ. (China)","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Beijing Key Lab. of Digital Media (China)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036886150","display_name":"Danpei Zhao","orcid":"https://orcid.org/0000-0001-6701-0471","observed_orcids":["https://orcid.org/0000-0001-6701-0471"]},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danpei Zhao","raw_affiliation_strings":["Beihang Univ. (China)","Beijing Key Lab. of Digital Media (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang Univ. (China)","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Beijing Key Lab. of Digital Media (China)","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016853247","display_name":"Zhiguo Jiang","orcid":"https://orcid.org/0000-0001-8786-2540","observed_orcids":["https://orcid.org/0000-0001-8786-2540"]},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiguo Jiang","raw_affiliation_strings":["Beihang Univ. (China)","Beijing Key Lab. of Digital Media (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang Univ. (China)","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Beijing Key Lab. of Digital Media (China)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9813","issue":null,"first_page":"98130V","last_page":"98130V"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.7348999977111816,"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":0.7348999977111816,"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":0.09749999642372131,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.05530000105500221,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/sparse-coding","display_name":"sparse coding","score":0.8939999938011169},{"id":"https://openalex.org/keywords/image-representation","display_name":"image representation","score":0.9440000057220459},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"dictionary learning","score":0.7260000109672546},{"id":"https://openalex.org/keywords/non-orthogonal-bases","display_name":"non-orthogonal bases","score":0.8320000171661377},{"id":"https://openalex.org/keywords/sparse-coefficients","display_name":"sparse coefficients","score":0.6470000147819519},{"id":"https://openalex.org/keywords/image-clustering","display_name":"image clustering","score":0.7829999923706055}],"concepts":[{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.8691942691802979},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.785262942314148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6388647556304932},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.573989748954773},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5652565360069275},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.529888927936554},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5240191221237183},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5063158273696899},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5010700225830078},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45728275179862976},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43799087405204773},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.41455695033073425},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41017264127731323},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2576146125793457},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2204911","doi":"https://doi.org/10.1117/12.2204911","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2204911","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W228380312","https://openalex.org/W1504194272","https://openalex.org/W1902027874","https://openalex.org/W1999174140","https://openalex.org/W2004544971","https://openalex.org/W2013029404","https://openalex.org/W2065030431","https://openalex.org/W2069959554","https://openalex.org/W2093323596","https://openalex.org/W2113606819","https://openalex.org/W2114748345","https://openalex.org/W2127271355","https://openalex.org/W2130187411","https://openalex.org/W2132467081","https://openalex.org/W2135046866","https://openalex.org/W2141607429","https://openalex.org/W2169658215","https://openalex.org/W4289709539","https://openalex.org/W6629992195"],"related_works":["https://openalex.org/W2263359957","https://openalex.org/W275503268","https://openalex.org/W2415184100","https://openalex.org/W2552089492","https://openalex.org/W2792870967","https://openalex.org/W1823262819","https://openalex.org/W2157639439","https://openalex.org/W2122518098","https://openalex.org/W2795890526","https://openalex.org/W1972483092"],"abstract_inverted_index":{"Sparse":[0,67],"coding":[1,39,63],"exhibits":[2],"good":[3],"performance":[4],"in":[5,24],"many":[6],"computer":[7],"vision":[8],"applications":[9],"by":[10,93],"finding":[11],"bases":[12,35],"which":[13,46],"capture":[14],"highlevel":[15],"semantics":[16],"of":[17,26,119,126],"the":[18,27,32,43,78,84,91,95,100,117,124],"data":[19],"and":[20,77,98,122],"learning":[21],"sparse":[22,38,62],"coefficients":[23,72],"terms":[25],"bases.":[28],"However,":[29],"due":[30],"to":[31,83,102],"fact":[33],"that":[34,112],"are":[36],"non-orthogonal,":[37],"can":[40,115],"hardly":[41],"preserve":[42,116],"samples\u2019":[44],"similarity,":[45],"is":[47,65,81],"important":[48],"for":[49,86],"discrimination.":[50],"In":[51],"this":[52,87],"paper,":[53],"a":[54],"new":[55],"image":[56,109],"representing":[57],"method":[58,114],"called":[59],"maximum":[60,97],"constrained":[61],"(MCSC)":[64],"proposed.":[66],"representation":[68],"with":[69],"more":[70,74],"active":[71],"means":[73],"similarity":[75,118],"information,":[76],"infinite":[79],"norm":[80],"added":[82],"solution":[85],"purpose.":[88],"We":[89],"solve":[90],"optimizer":[92],"constraining":[94],"codes\u2019":[96],"releasing":[99],"residual":[101],"other":[103],"dictionary":[104],"atoms.":[105],"Experimental":[106],"results":[107],"on":[108],"clustering":[110],"show":[111],"our":[113],"adjacent":[120],"samples":[121],"maintain":[123],"sparsity":[125],"code":[127],"simultaneously.":[128]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}