{"id":"https://openalex.org/W4296378254","doi":"https://doi.org/10.2298/csis220321040t","title":"BiSeNet-oriented context attention model for image semantic segmentation","display_name":"BiSeNet-oriented context attention model for image semantic segmentation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296378254","doi":"https://doi.org/10.2298/csis220321040t"},"language":"en","primary_location":{"id":"doi:10.2298/csis220321040t","is_oa":true,"landing_page_url":"https://doi.org/10.2298/csis220321040t","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142200040T","source":{"id":"https://openalex.org/S206939107","display_name":"Computer Science and Information Systems","issn_l":"1820-0214","issn":["1820-0214","2406-1018"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321031","host_organization_name":"ComSIS Consortium","host_organization_lineage":["https://openalex.org/P4310321031"],"host_organization_lineage_names":["ComSIS Consortium"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science and Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142200040T","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010369192","display_name":"Lin Teng","orcid":"https://orcid.org/0000-0002-3437-2123"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Teng","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University Harbin, China","College of Information and Communication Engineering, Harbin Engineering University Harbin 150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University Harbin, China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088835989","display_name":"Yulong Qiao","orcid":"https://orcid.org/0000-0002-5821-5210"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulong Qiao","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University Harbin, China","College of Information and Communication Engineering, Harbin Engineering University Harbin 150001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University Harbin, China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University Harbin 150001, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":null,"apc_paid":null,"fwci":1.0528,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.76086846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"19","issue":"3","first_page":"1409","last_page":"1426"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.991100013256073,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8674703240394592},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.758284330368042},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6674777269363403},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6323130130767822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6195359826087952},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5860271453857422},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5434809327125549},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5394362807273865},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5063756704330444},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.4897782802581787},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.47138839960098267},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4682613015174866},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4596864879131317},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.4559631049633026},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4318813383579254}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8674703240394592},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.758284330368042},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6674777269363403},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6323130130767822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6195359826087952},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5860271453857422},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5434809327125549},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5394362807273865},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5063756704330444},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.4897782802581787},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.47138839960098267},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4682613015174866},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4596864879131317},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.4559631049633026},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4318813383579254},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2298/csis220321040t","is_oa":true,"landing_page_url":"https://doi.org/10.2298/csis220321040t","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142200040T","source":{"id":"https://openalex.org/S206939107","display_name":"Computer Science and Information Systems","issn_l":"1820-0214","issn":["1820-0214","2406-1018"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321031","host_organization_name":"ComSIS Consortium","host_organization_lineage":["https://openalex.org/P4310321031"],"host_organization_lineage_names":["ComSIS Consortium"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science and Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.2298/csis220321040t","is_oa":true,"landing_page_url":"https://doi.org/10.2298/csis220321040t","pdf_url":"http://www.doiserbia.nb.rs/ft.aspx?id=1820-02142200040T","source":{"id":"https://openalex.org/S206939107","display_name":"Computer Science and Information Systems","issn_l":"1820-0214","issn":["1820-0214","2406-1018"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310321031","host_organization_name":"ComSIS Consortium","host_organization_lineage":["https://openalex.org/P4310321031"],"host_organization_lineage_names":["ComSIS Consortium"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science and Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296378254.pdf","grobid_xml":"https://content.openalex.org/works/W4296378254.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W2560023338","https://openalex.org/W2886934227","https://openalex.org/W2921781974","https://openalex.org/W2955058313","https://openalex.org/W2964309882","https://openalex.org/W2970422778","https://openalex.org/W2999921958","https://openalex.org/W3007475496","https://openalex.org/W3009707803","https://openalex.org/W3034681889","https://openalex.org/W3037654234","https://openalex.org/W3038023776","https://openalex.org/W3080085375","https://openalex.org/W3088873647","https://openalex.org/W3095198472","https://openalex.org/W3097161036","https://openalex.org/W3097623989","https://openalex.org/W3109581785","https://openalex.org/W3110089052","https://openalex.org/W3120123272","https://openalex.org/W3125553402","https://openalex.org/W3128408141","https://openalex.org/W3130508033","https://openalex.org/W3131342469","https://openalex.org/W3131457191","https://openalex.org/W3131594276","https://openalex.org/W3135698299","https://openalex.org/W3138049223","https://openalex.org/W3142871063","https://openalex.org/W3142876798","https://openalex.org/W3159420753","https://openalex.org/W3162362121","https://openalex.org/W3163634825","https://openalex.org/W3165688842","https://openalex.org/W3176368462","https://openalex.org/W3182850645","https://openalex.org/W3186482562","https://openalex.org/W3188836801","https://openalex.org/W3199004359","https://openalex.org/W3203573502","https://openalex.org/W3210710412","https://openalex.org/W4200109102","https://openalex.org/W4200398616","https://openalex.org/W4366574399"],"related_works":["https://openalex.org/W134976887","https://openalex.org/W2021143974","https://openalex.org/W2549765251","https://openalex.org/W1840273037","https://openalex.org/W1582206143","https://openalex.org/W2162802639","https://openalex.org/W2117933325","https://openalex.org/W2464972745","https://openalex.org/W2370049162","https://openalex.org/W2588703147"],"abstract_inverted_index":{"When":[0],"the":[1,8,18,25,30,48,50,62,85,91,96,102,114,139,145,152],"traditional":[2],"semantic":[3,45,80,133],"segmentation":[4,31,98,134,154],"model":[5,42],"is":[6,15,53,74,88],"adopted,":[7],"different":[9],"feature":[10,13,19,142,148],"importance":[11],"of":[12,64,82,141,147],"maps":[14],"ignored":[16],"in":[17,24,67],"extraction":[20],"stage,":[21],"which":[22],"results":[23,115],"detail":[26],"loss,":[27],"and":[28,113,123,150],"affects":[29],"effect.":[32,155],"In":[33,47],"this":[34],"paper,":[35],"we":[36,106],"propose":[37],"a":[38],"BiSeNet-oriented":[39],"context":[40],"attention":[41,72],"for":[43],"image":[44],"segmentation.":[46],"BiSeNet,":[49],"spatial":[51],"path":[52],"utilized":[54],"to":[55,60,76,94],"extract":[56],"more":[57],"low-level":[58],"features":[59,81],"solve":[61],"problem":[63],"information":[65],"loss":[66,87,92,146],"deep":[68],"network":[69],"layers.":[70],"Context":[71],"mechanism":[73],"used":[75,89],"mine":[77],"high-level":[78],"implied":[79],"images.":[83],"Meanwhile,":[84],"focus":[86],"as":[90],"function":[93],"improve":[95],"final":[97,153],"effect":[99],"by":[100],"reducing":[101],"internal":[103],"weighting.":[104],"Finally,":[105],"conduct":[107],"experiments":[108],"on":[109],"open":[110],"data":[111],"sets,":[112],"show":[116],"that":[117],"pixel":[118,121],"accuracy,":[119,122],"average":[120,124],"Intersection-over-Union":[125],"are":[126],"greatly":[127],"improved":[128],"compared":[129],"with":[130],"other":[131],"state-of-theart":[132],"models.":[135],"It":[136],"effectively":[137],"improves":[138,151],"accuracy":[140],"extraction,":[143],"reduces":[144],"details,":[149]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":9}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}