{"id":"https://openalex.org/W4309097652","doi":"https://doi.org/10.1109/tnnls.2022.3219245","title":"DAGCN: Dynamic and Adaptive Graph Convolutional Network for Salient Object Detection","display_name":"DAGCN: Dynamic and Adaptive Graph Convolutional Network for Salient Object Detection","publication_year":2022,"publication_date":"2022-11-14","ids":{"openalex":"https://openalex.org/W4309097652","doi":"https://doi.org/10.1109/tnnls.2022.3219245","pmid":"https://pubmed.ncbi.nlm.nih.gov/36374896"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3219245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3219245","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5029512731","display_name":"Ce Li","orcid":"https://orcid.org/0000-0002-4627-6112"},"institutions":[{"id":"https://openalex.org/I22716506","display_name":"Lanzhou University of Technology","ror":"https://ror.org/03panb555","country_code":"CN","type":"education","lineage":["https://openalex.org/I22716506"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ce Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4627-6112","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China","institution_ids":["https://openalex.org/I22716506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100325258","display_name":"Fenghua Liu","orcid":"https://orcid.org/0000-0002-7634-8893"},"institutions":[{"id":"https://openalex.org/I22716506","display_name":"Lanzhou University of Technology","ror":"https://ror.org/03panb555","country_code":"CN","type":"education","lineage":["https://openalex.org/I22716506"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fenghua Liu","raw_affiliation_strings":["College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7634-8893","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China","institution_ids":["https://openalex.org/I22716506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020301327","display_name":"Zhiqiang Tian","orcid":"https://orcid.org/0000-0002-3669-3748"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Tian","raw_affiliation_strings":["School of Software Engineering, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-3669-3748","affiliations":[{"raw_affiliation_string":"School of Software Engineering, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044668212","display_name":"Shaoyi Du","orcid":"https://orcid.org/0000-0002-7092-0596"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoyi Du","raw_affiliation_strings":["Institute of Artificial Intelligence and Robotics, College of Artificial Intelligence, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-7092-0596","affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Robotics, College of Artificial Intelligence, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100741279","display_name":"Yang Wu","orcid":"https://orcid.org/0000-0001-8010-6857"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Wu","raw_affiliation_strings":["ARC Laboratory, Tencent PCG, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-8010-6857","affiliations":[{"raw_affiliation_string":"ARC Laboratory, Tencent PCG, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9364,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.92560005,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"35","issue":"6","first_page":"7612","last_page":"7626"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9836000204086304,"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":0.7151689529418945},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6004101037979126},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5033876299858093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4924705922603607},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4743931293487549},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4185613691806793},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40350809693336487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7151689529418945},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6004101037979126},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5033876299858093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4924705922603607},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4743931293487549},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4185613691806793},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40350809693336487},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3219245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3219245","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:36374896","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36374896","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1193541440","display_name":null,"funder_award_id":"2020AAA0108100","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G833113359","display_name":"\u9762\u5411\u53d8\u6362\u57df\u7684\u89c6\u6ce8\u610f\u6df1\u5ea6\u5b66\u4e60\u611f\u77e5\u8ba1\u7b97\u53ca\u5176\u5e94\u7528\u7814\u7a76","funder_award_id":"61866022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8396617935","display_name":"\u57fa\u4e8e\u56fe\u50cf\u70b9\u96c6\u914d\u51c6\u7684\u9ad8\u7cbe\u5ea6\u5927\u8303\u56f4\u4ea4\u901a\u573a\u666f\u4e09\u7ef4\u91cd\u5efa\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971343","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1772076007","https://openalex.org/W1894057436","https://openalex.org/W2001070843","https://openalex.org/W2002781701","https://openalex.org/W2007534788","https://openalex.org/W2011900468","https://openalex.org/W2039313011","https://openalex.org/W2047670868","https://openalex.org/W2065985528","https://openalex.org/W2086791339","https://openalex.org/W2098702446","https://openalex.org/W2116341502","https://openalex.org/W2121927366","https://openalex.org/W2128272608","https://openalex.org/W2130147475","https://openalex.org/W2135957164","https://openalex.org/W2171378720","https://openalex.org/W2194775991","https://openalex.org/W2293332611","https://openalex.org/W2395611524","https://openalex.org/W2461475918","https://openalex.org/W2470270897","https://openalex.org/W2518770889","https://openalex.org/W2605929543","https://openalex.org/W2740667773","https://openalex.org/W2744613561","https://openalex.org/W2744876417","https://openalex.org/W2776855315","https://openalex.org/W2798791651","https://openalex.org/W2799074129","https://openalex.org/W2883638665","https://openalex.org/W2884555738","https://openalex.org/W2895251968","https://openalex.org/W2955147859","https://openalex.org/W2963017945","https://openalex.org/W2963032190","https://openalex.org/W2963084622","https://openalex.org/W2963299740","https://openalex.org/W2963319519","https://openalex.org/W2963685207","https://openalex.org/W2963706010","https://openalex.org/W2964321699","https://openalex.org/W2968392770","https://openalex.org/W2987391422","https://openalex.org/W2990984982","https://openalex.org/W3015304398","https://openalex.org/W3034345703","https://openalex.org/W3034453930","https://openalex.org/W3034684132","https://openalex.org/W3035290198","https://openalex.org/W3035666869","https://openalex.org/W3084512379","https://openalex.org/W3096966254","https://openalex.org/W3107944836","https://openalex.org/W3109623941","https://openalex.org/W3162363705","https://openalex.org/W3173382343","https://openalex.org/W3200022718","https://openalex.org/W4225487034","https://openalex.org/W4239147634","https://openalex.org/W4313025803","https://openalex.org/W4313170506","https://openalex.org/W4385245566","https://openalex.org/W6637373629","https://openalex.org/W6726873649","https://openalex.org/W6747043858","https://openalex.org/W6754929296","https://openalex.org/W6766273390"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2369710579","https://openalex.org/W4327728159","https://openalex.org/W4394266730","https://openalex.org/W1990856605","https://openalex.org/W2053783616","https://openalex.org/W2545348020","https://openalex.org/W2293263892"],"abstract_inverted_index":{"Deep-learning-based":[0],"salient":[1],"object":[2],"detection":[3],"(SOD)":[4],"has":[5,156],"achieved":[6],"significant":[7],"success":[8],"in":[9,31,141],"recent":[10],"years.":[11],"The":[12,85,103,123,154,176],"SOD":[13,57],"focuses":[14],"on":[15,220],"the":[16,20,28,32,35,100,106,110,115,127,136,139,142,157,161,169,174,179,186,191,193,196,201],"context":[17,29,45,112,128,150],"modeling":[18,148],"of":[19,70,109,138,149,173,178],"scene":[21,33],"information,":[22],"and":[23,47,61,79,98,145,165,225],"how":[24],"to":[25,41,96,159,168,190,207],"effectively":[26,228],"model":[27,48,97,155,194],"relationship":[30,108,129,181],"is":[34,39,68,87,94,182],"key.":[36],"However,":[37],"it":[38],"difficult":[40],"build":[42],"an":[43],"effective":[44],"structure":[46,197],"it.":[49],"In":[50],"this":[51],"article,":[52],"we":[53],"propose":[54],"a":[55,120,131],"novel":[56,88],"method":[58,125],"called":[59],"dynamic":[60],"adaptive":[62,73,89],"graph":[63,75,91,133,202,209],"convolutional":[64,76,187],"network":[65,77],"(DAGCN)":[66],"that":[67,214],"composed":[69],"two":[71],"parts,":[72],"neighborhood-wise":[74,90],"(AnwGCN)":[78],"spatially":[80],"restricted":[81],"K-nearest":[82],"neighbors":[83],"(SRKNN).":[84],"AnwGCN":[86],"convolution,":[92],"which":[93],"used":[95,223],"analyze":[99],"saliency":[101,111],"context.":[102],"SRKNN":[104],"constructs":[105,126],"topological":[107,132],"by":[113,134],"measuring":[114,135],"non-Euclidean":[116,143],"spatial":[117],"distance":[118,137],"within":[119],"limited":[121],"range.":[122],"proposed":[124],"as":[130],"features":[140,164],"space,":[144],"conducts":[146],"comparative":[147],"information":[151],"through":[152],"AnwGCN.":[153],"ability":[158],"learn":[160],"metrics":[162],"from":[163],"can":[166,205,226],"adapt":[167,206],"hidden":[170],"space":[171],"distribution":[172],"data.":[175,210],"description":[177],"feature":[180],"more":[183],"accurate.":[184],"Through":[185],"kernel":[188],"adapted":[189],"neighborhood,":[192],"obtains":[195],"learning":[198],"ability.":[199],"Therefore,":[200],"convolution":[203],"process":[204],"different":[208],"Experimental":[211],"results":[212],"demonstrate":[213],"our":[215],"solution":[216],"achieves":[217],"satisfactory":[218],"performance":[219],"six":[221],"widely":[222],"datasets":[224],"also":[227],"detect":[229],"camouflaged":[230],"objects.":[231],"Our":[232],"code":[233],"will":[234],"be":[235],"available":[236],"at:":[237],"https://github.com/CSIM-LUT/DAGCN.git.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}