{"id":"https://openalex.org/W4287009164","doi":"https://doi.org/10.1007/s00371-022-02597-w","title":"QCNet: query context network for salient object detection of automatic surface inspection","display_name":"QCNet: query context network for salient object detection of automatic surface inspection","publication_year":2022,"publication_date":"2022-07-25","ids":{"openalex":"https://openalex.org/W4287009164","doi":"https://doi.org/10.1007/s00371-022-02597-w"},"language":"en","primary_location":{"id":"doi:10.1007/s00371-022-02597-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00371-022-02597-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00371-022-02597-w.pdf","source":{"id":"https://openalex.org/S73060445","display_name":"The Visual Computer","issn_l":"0178-2789","issn":["0178-2789","1432-2315"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Visual Computer","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00371-022-02597-w.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084778521","display_name":"Jie Sun","orcid":"https://orcid.org/0000-0002-6470-9452"},"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":"Jie Sun","raw_affiliation_strings":["Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China","State Key Laboratory of Fluid Power and Mechatronic System, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"State Key Laboratory of Fluid Power and Mechatronic System, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087776565","display_name":"Senbo Yan","orcid":"https://orcid.org/0000-0002-5051-0506"},"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":"Senbo Yan","raw_affiliation_strings":["State Key Lab of CAD &CG, College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Lab of CAD &CG, College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044266797","display_name":"Xiaowen Song","orcid":"https://orcid.org/0000-0001-6386-9836"},"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":true,"raw_author_name":"Xiaowen Song","raw_affiliation_strings":["Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China","State Key Laboratory of Fluid Power and Mechatronic System, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China"],"raw_orcid":"https://orcid.org/0000-0001-6386-9836","affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"State Key Laboratory of Fluid Power and Mechatronic System, School of Mechanical Engineering, Zhejiang University, Hangzhou, 310027, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5044266797"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.972,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.74206813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"39","issue":"10","first_page":"4391","last_page":"4403"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9787999987602234,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/computer-science","display_name":"Computer science","score":0.8225301504135132},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.7122454643249512},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6647602915763855},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6439542174339294},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6421294212341309},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6286634802818298},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5773491859436035},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5647931694984436},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5178656578063965},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46585163474082947},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4313649833202362},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.421347439289093}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8225301504135132},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.7122454643249512},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6647602915763855},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6439542174339294},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6421294212341309},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6286634802818298},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5773491859436035},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5647931694984436},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5178656578063965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46585163474082947},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4313649833202362},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.421347439289093},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s00371-022-02597-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00371-022-02597-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00371-022-02597-w.pdf","source":{"id":"https://openalex.org/S73060445","display_name":"The Visual Computer","issn_l":"0178-2789","issn":["0178-2789","1432-2315"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Visual Computer","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s00371-022-02597-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00371-022-02597-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00371-022-02597-w.pdf","source":{"id":"https://openalex.org/S73060445","display_name":"The Visual Computer","issn_l":"0178-2789","issn":["0178-2789","1432-2315"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Visual Computer","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5267378748","display_name":null,"funder_award_id":"No. 91948301","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6697783626","display_name":null,"funder_award_id":"91948301","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7242979491","display_name":null,"funder_award_id":"51821093","funder_id":"https://openalex.org/F4320322271","funder_display_name":"Science Fund for Creative Research Groups"},{"id":"https://openalex.org/G7537661496","display_name":null,"funder_award_id":"Grant No. 91948301","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/F4320322271","display_name":"Science Fund for Creative Research Groups","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4287009164.pdf","grobid_xml":"https://content.openalex.org/works/W4287009164.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W845365781","https://openalex.org/W1677182931","https://openalex.org/W1772076007","https://openalex.org/W1903029394","https://openalex.org/W1974971113","https://openalex.org/W1975864646","https://openalex.org/W1986306729","https://openalex.org/W2002781701","https://openalex.org/W2012496675","https://openalex.org/W2039313011","https://openalex.org/W2060095179","https://openalex.org/W2065985528","https://openalex.org/W2072611278","https://openalex.org/W2086791339","https://openalex.org/W2108598243","https://openalex.org/W2121679663","https://openalex.org/W2131191563","https://openalex.org/W2158535435","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2461475918","https://openalex.org/W2546160422","https://openalex.org/W2592939477","https://openalex.org/W2740667773","https://openalex.org/W2744613561","https://openalex.org/W2753588254","https://openalex.org/W2790914279","https://openalex.org/W2807746031","https://openalex.org/W2808442315","https://openalex.org/W2888407265","https://openalex.org/W2904559969","https://openalex.org/W2907868778","https://openalex.org/W2919115771","https://openalex.org/W2939217524","https://openalex.org/W2944303778","https://openalex.org/W2944503515","https://openalex.org/W2948510860","https://openalex.org/W2961348656","https://openalex.org/W2963112696","https://openalex.org/W2963299740","https://openalex.org/W2963418739","https://openalex.org/W2963529609","https://openalex.org/W2963685207","https://openalex.org/W2963868681","https://openalex.org/W2964308596","https://openalex.org/W2990984982","https://openalex.org/W2992171550","https://openalex.org/W2994615081","https://openalex.org/W2996001414","https://openalex.org/W3007572768","https://openalex.org/W3025800305","https://openalex.org/W3112885960","https://openalex.org/W3117530986","https://openalex.org/W3136838953","https://openalex.org/W4239147634","https://openalex.org/W6604662147"],"related_works":["https://openalex.org/W2922421953","https://openalex.org/W3002270006","https://openalex.org/W1504288058","https://openalex.org/W2577364290","https://openalex.org/W3038672259","https://openalex.org/W2608348068","https://openalex.org/W1970041046","https://openalex.org/W2075973707","https://openalex.org/W2497633036","https://openalex.org/W2161193411"],"abstract_inverted_index":{"Abstract":[0],"Building":[1],"upon":[2],"fully":[3,158],"convolutional":[4,159],"networks":[5],"(FCNs),":[6],"deep":[7],"learning-based":[8],"salient":[9,71,88],"object":[10,35,72],"detection":[11,68,143],"(SOD)":[12],"methods":[13,29,40,139],"achieve":[14],"gratifying":[15],"performance":[16],"in":[17,58,156],"many":[18],"vision":[19],"tasks,":[20],"including":[21],"surface":[22,141],"defect":[23,142],"detection.":[24,73,170],"However,":[25],"most":[26],"existing":[27],"FCN-based":[28],"still":[30],"suffer":[31],"from":[32,105],"the":[33,59,82,106,113,119,131,137,166],"coarse":[34],"edge":[36],"predictions.":[37,126],"The":[38],"state-of-the-art":[39,138],"employ":[41],"intricate":[42],"feature":[43,84],"aggregation":[44],"techniques":[45],"to":[46,56,85,96,116],"refine":[47],"boundaries,":[48],"but":[49],"they":[50],"are":[51,93],"often":[52],"too":[53],"computational":[54],"cost":[55],"deploy":[57],"real":[60],"application.":[61],"This":[62],"paper":[63],"proposes":[64],"a":[65,157],"semantics":[66],"guided":[67],"paradigm":[69],"for":[70,168],"Guided":[74],"atrous":[75],"pyramid":[76],"module":[77],"is":[78],"first":[79],"applied":[80],"on":[81,140],"top":[83],"segment":[86],"complete":[87],"semantics.":[89],"Query":[90],"context":[91],"modules":[92,111],"further":[94],"used":[95],"build":[97],"relation":[98],"maps":[99],"between":[100],"saliency":[101,125],"and":[102,144],"structural":[103],"information":[104],"top-down":[107],"pathway.":[108],"These":[109],"two":[110],"allow":[112],"semantic":[114],"features":[115],"flow":[117],"throughout":[118],"decoder":[120],"phase,":[121],"yielding":[122],"detail":[123],"enriched":[124],"Experimental":[127],"results":[128],"demonstrate":[129],"that":[130],"proposed":[132],"method":[133,150],"performs":[134],"favorably":[135],"against":[136],"SOD":[145],"benchmarks.":[146],"In":[147],"addition,":[148],"this":[149],"can":[151],"detect":[152],"at":[153],"27":[154],"FPS":[155],"fashion":[160],"without":[161],"any":[162],"post-processing,":[163],"which":[164],"has":[165],"potential":[167],"real-time":[169]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
