{"id":"https://openalex.org/W2970672451","doi":"https://doi.org/10.1109/icip.2019.8803557","title":"Learning the Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks","display_name":"Learning the Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970672451","doi":"https://doi.org/10.1109/icip.2019.8803557","mag":"2970672451"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","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/A5038081609","display_name":"Haoliang Sun","orcid":"https://orcid.org/0000-0001-7715-5682"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoliang Sun","raw_affiliation_strings":["Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026486701","display_name":"Xiantong Zhen","orcid":"https://orcid.org/0000-0001-5213-0462"},"institutions":[{"id":"https://openalex.org/I4210116052","display_name":"Inception Institute of Artificial Intelligence","ror":"https://ror.org/02664zk40","country_code":"AE","type":"facility","lineage":["https://openalex.org/I4210116052"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Xiantong Zhen","raw_affiliation_strings":["Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210116052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100672586","display_name":"Yilong Yin","orcid":"https://orcid.org/0000-0001-8341-8792"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilong Yin","raw_affiliation_strings":["Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2187,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.52084874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9962999820709229,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9962999820709229,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9962000250816345,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7500789165496826},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5267611742019653},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.504179835319519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4731113612651825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3994169533252716},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34689879417419434}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7500789165496826},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5267611742019653},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.504179835319519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4731113612651825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3994169533252716},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34689879417419434},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803557","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W566612420","https://openalex.org/W1506778248","https://openalex.org/W1862697533","https://openalex.org/W1900408618","https://openalex.org/W1922045146","https://openalex.org/W1928812244","https://openalex.org/W1968678306","https://openalex.org/W2066986622","https://openalex.org/W2068935349","https://openalex.org/W2084146405","https://openalex.org/W2084269393","https://openalex.org/W2112074816","https://openalex.org/W2120453412","https://openalex.org/W2126017757","https://openalex.org/W2142172505","https://openalex.org/W2144093206","https://openalex.org/W2150600350","https://openalex.org/W2167581801","https://openalex.org/W2171837816","https://openalex.org/W2432877789","https://openalex.org/W2739937239","https://openalex.org/W2752749390","https://openalex.org/W2788919350","https://openalex.org/W2905224888","https://openalex.org/W2963559058","https://openalex.org/W6615889216","https://openalex.org/W6680889708","https://openalex.org/W6757374366"],"related_works":["https://openalex.org/W3188962172","https://openalex.org/W2772917594","https://openalex.org/W4306742369","https://openalex.org/W4303457083","https://openalex.org/W2131146434","https://openalex.org/W4376623224","https://openalex.org/W2951359407","https://openalex.org/W3136979370","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Image-set":[0],"classification":[1,14,17,47],"has":[2],"recently":[3],"made":[4],"great":[5,19,152],"progress":[6],"in":[7,105,154],"computer":[8],"vision.":[9],"Compared":[10],"with":[11],"traditional":[12],"image":[13,38,45,78,156],"tasks,":[15],"set-based":[16,155],"exhibits":[18],"challenges":[20],"due":[21],"to":[22,35,71,89,100,112,129],"huge":[23],"intra-class":[24],"variability":[25],"and":[26,43,108],"high":[27],"inter-class":[28],"ambiguity.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,60,121],"propose":[34,122],"model":[36,137],"the":[37,49,56,62,68,73,81,92,103,114,118,124,136],"set":[39,46,106],"as":[40,48],"a":[41],"graph":[42,50,65,74,96,109],"formulate":[44],"matching":[51],"task.":[52],"Without":[53],"relying":[54],"on":[55],"strong":[57],"structure":[58,75],"assumption,":[59],"build":[61],"first":[63],"end-to-end":[64],"convolutional":[66,86,97],"network,":[67],"Deep":[69],"SetNet,":[70],"learn":[72,102],"of":[76,84],"an":[77],"set.":[79],"Specifically,":[80],"SetNet":[82],"consists":[83],"one":[85,95],"network":[87],"(CNN)":[88],"sufficiently":[90],"extract":[91],"discriminative":[93],"vertex,":[94],"Network":[98],"(GCN)":[99],"faithfully":[101],"substructure":[104],"graphs":[107],"pooling":[110],"layers":[111],"aggregate":[113],"vertex":[115,131],"features":[116],"from":[117],"GCN.":[119],"Moreover,":[120],"imposing":[123],"\u21131,2-norm":[125],"based":[126],"sparsity":[127],"constraint":[128],"select":[130],"features,":[132],"which":[133],"largely":[134],"improves":[135],"generalization":[138],"capability.":[139],"Extensive":[140],"experiments":[141],"demonstrate":[142],"that":[143],"our":[144],"method":[145],"consistently":[146],"outperforms":[147],"state-of-the-art":[148],"methods,":[149],"showing":[150],"its":[151],"effectiveness":[153],"classification.":[157]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
