{"id":"https://openalex.org/W2040808808","doi":"https://doi.org/10.1109/icip.2011.6116550","title":"Learning structural conjunction of image content by sparse graphical model","display_name":"Learning structural conjunction of image content by sparse graphical model","publication_year":2011,"publication_date":"2011-09-01","ids":{"openalex":"https://openalex.org/W2040808808","doi":"https://doi.org/10.1109/icip.2011.6116550","mag":"2040808808"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2011.6116550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2011.6116550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 18th IEEE International Conference on Image Processing","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/A5100367955","display_name":"Donghui Wang","orcid":"https://orcid.org/0000-0002-1198-0978"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghui Wang","raw_affiliation_strings":["Institute of Artificial Intelligence, University of Zhejiang, Hangzhou, China","Institute of Artificial Intelligence, Zhejiang University, Hangzhou, China 310027"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence, University of Zhejiang, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Institute of Artificial Intelligence, Zhejiang University, Hangzhou, China 310027","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058372120","display_name":"Xiao Deng","orcid":"https://orcid.org/0000-0001-5499-1258"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Deng","raw_affiliation_strings":["Institute of Artificial Intelligence, University of Zhejiang, Hangzhou, China","Institute of Artificial Intelligence, Zhejiang University, Hangzhou, China 310027"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence, University of Zhejiang, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Institute of Artificial Intelligence, Zhejiang University, Hangzhou, China 310027","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"45","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":1.0,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":1.0,"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/T12364","display_name":"Archaeological Research and Protection","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/1912","display_name":"Space and Planetary Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11212","display_name":"Cultural Heritage Materials Analysis","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/conjunction","display_name":"Conjunction (astronomy)","score":0.7616593837738037},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6933038234710693},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.6851347088813782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5408675074577332},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.4964039921760559},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.475460946559906},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.43371817469596863},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.4333493113517761},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.43304115533828735},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.411079466342926},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4086989164352417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40333640575408936},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3234846591949463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19948825240135193}],"concepts":[{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.7616593837738037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6933038234710693},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.6851347088813782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5408675074577332},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.4964039921760559},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.475460946559906},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.43371817469596863},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.4333493113517761},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.43304115533828735},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.411079466342926},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4086989164352417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40333640575408936},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3234846591949463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19948825240135193},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2011.6116550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2011.6116550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 18th IEEE International Conference on Image Processing","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":9,"referenced_works":["https://openalex.org/W1984568490","https://openalex.org/W2010824638","https://openalex.org/W2055430302","https://openalex.org/W2112814716","https://openalex.org/W2205290124","https://openalex.org/W2494084875","https://openalex.org/W3048946968","https://openalex.org/W3098834468","https://openalex.org/W3165771198"],"related_works":["https://openalex.org/W2001490496","https://openalex.org/W2182544397","https://openalex.org/W3083599310","https://openalex.org/W2616545131","https://openalex.org/W2962993057","https://openalex.org/W2142063839","https://openalex.org/W3044018691","https://openalex.org/W4385373568","https://openalex.org/W2091883426","https://openalex.org/W3173235360"],"abstract_inverted_index":{"In":[0],"this":[1,83],"paper":[2],"we":[3],"present":[4],"a":[5],"novel":[6],"method":[7],"on":[8],"learning":[9],"structural":[10,77,89],"conjunction":[11,78],"of":[12,79,87],"image":[13,92,100],"content":[14],"by":[15,98],"sparse":[16,41,47],"graphical":[17,43],"model.":[18],"We":[19,81],"first":[20],"use":[21],"matrix-variate":[22],"distributions":[23],"to":[24,40,85],"formulate":[25],"two":[26],"statistical":[27],"structure":[28,62,69],"models":[29,44],"and":[30,68,94],"establish":[31],"the":[32,96],"connection":[33,37],"between":[34,91],"them.":[35],"The":[36],"leads":[38],"us":[39],"Gaussian":[42],"in":[45],"which":[46],"regression":[48],"technique":[49],"such":[50],"as":[51,59,61],"lasso":[52],"is":[53],"used":[54],"for":[55,75],"concentration":[56],"matrix":[57],"estimation":[58],"well":[60],"learning.":[63],"Our":[64],"proposed":[65],"theoretical":[66],"framework":[67],"selection":[70],"methods":[71],"provide":[72],"an":[73],"approach":[74,84],"exploiting":[76],"data.":[80],"apply":[82],"construction":[86],"underlying":[88],"correlation":[90],"content,":[93],"demonstrate":[95],"effectiveness":[97],"solving":[99],"jigsaw":[101],"problem.":[102]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}