{"id":"https://openalex.org/W4386799137","doi":"https://doi.org/10.1155/2023/1616055","title":"TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross\u2010Task Consistency","display_name":"TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross\u2010Task Consistency","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386799137","doi":"https://doi.org/10.1155/2023/1616055"},"language":"en","primary_location":{"id":"doi:10.1155/2023/1616055","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2023/1616055","pdf_url":"https://downloads.hindawi.com/journals/ijis/2023/1616055.pdf","source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/ijis/2023/1616055.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101952574","display_name":"Dan Zhang","orcid":"https://orcid.org/0000-0001-8523-7944"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Zhang","raw_affiliation_strings":["Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing","Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101992412","display_name":"Rui Zheng","orcid":"https://orcid.org/0000-0003-1028-7909"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Zheng","raw_affiliation_strings":["Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing","Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing","institution_ids":["https://openalex.org/I145897649"]},{"raw_affiliation_string":"Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046657715","display_name":"Gadeng Luosang","orcid":"https://orcid.org/0009-0009-1873-3812"},"institutions":[{"id":"https://openalex.org/I140786321","display_name":"Tibet University","ror":"https://ror.org/05petvd47","country_code":"CN","type":"education","lineage":["https://openalex.org/I140786321"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gadeng Luosang","raw_affiliation_strings":["Department of Information Science and Technology, Tibet University, Lhasa 850012","Department of Information Science and Technology, Tibet University, Lhasa 850012, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Science and Technology, Tibet University, Lhasa 850012","institution_ids":["https://openalex.org/I140786321"]},{"raw_affiliation_string":"Department of Information Science and Technology, Tibet University, Lhasa 850012, China","institution_ids":["https://openalex.org/I140786321"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077769611","display_name":"Pei Yang","orcid":"https://orcid.org/0000-0003-2765-0401"},"institutions":[{"id":"https://openalex.org/I116265982","display_name":"Qinghai University","ror":"https://ror.org/05h33bt13","country_code":"CN","type":"education","lineage":["https://openalex.org/I116265982"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pei Yang","raw_affiliation_strings":["Department of Computer Technology and Application, Qinghai University, Xining 810016","Department of Computer Technology and Application, Qinghai University, Xining 810016, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Technology and Application, Qinghai University, Xining 810016","institution_ids":["https://openalex.org/I116265982"]},{"raw_affiliation_string":"Department of Computer Technology and Application, Qinghai University, Xining 810016, China","institution_ids":["https://openalex.org/I116265982"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101992412"],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":{"value":2500,"currency":"USD","value_usd":2500},"apc_paid":{"value":2500,"currency":"USD","value_usd":2500},"fwci":0.369,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60152698,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2023","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9990000128746033,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9988999962806702,"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":0.7499989867210388},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7296177744865417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6731853485107422},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6492843627929688},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6333409547805786},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5819985866546631},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.47504380345344543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46981576085090637},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.43543657660484314},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3803446292877197},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09582969546318054}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7499989867210388},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7296177744865417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6731853485107422},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6492843627929688},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6333409547805786},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5819985866546631},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.47504380345344543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46981576085090637},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.43543657660484314},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3803446292877197},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09582969546318054},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1155/2023/1616055","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2023/1616055","pdf_url":"https://downloads.hindawi.com/journals/ijis/2023/1616055.pdf","source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1155/2023/1616055","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2023/1616055","pdf_url":"https://downloads.hindawi.com/journals/ijis/2023/1616055.pdf","source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"},{"id":"https://openalex.org/F4320328117","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386799137.pdf"},"referenced_works_count":84,"referenced_works":["https://openalex.org/W586034241","https://openalex.org/W845365781","https://openalex.org/W1546771929","https://openalex.org/W1821462560","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1909234690","https://openalex.org/W1923697677","https://openalex.org/W2124592697","https://openalex.org/W2145023731","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2343077198","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2607333215","https://openalex.org/W2624871570","https://openalex.org/W2630837129","https://openalex.org/W2798441115","https://openalex.org/W2886934227","https://openalex.org/W2891601902","https://openalex.org/W2895401575","https://openalex.org/W2916798096","https://openalex.org/W2924464923","https://openalex.org/W2949847866","https://openalex.org/W2950103041","https://openalex.org/W2952787292","https://openalex.org/W2954054736","https://openalex.org/W2955058313","https://openalex.org/W2962772649","https://openalex.org/W2962802951","https://openalex.org/W2962850830","https://openalex.org/W2962851801","https://openalex.org/W2962872526","https://openalex.org/W2963091558","https://openalex.org/W2963122961","https://openalex.org/W2963125010","https://openalex.org/W2963150697","https://openalex.org/W2963163009","https://openalex.org/W2963263347","https://openalex.org/W2963307106","https://openalex.org/W2963418739","https://openalex.org/W2963498646","https://openalex.org/W2963677766","https://openalex.org/W2964021722","https://openalex.org/W2964217532","https://openalex.org/W2964309882","https://openalex.org/W2966401131","https://openalex.org/W2968136324","https://openalex.org/W2972321983","https://openalex.org/W2989684653","https://openalex.org/W2991471181","https://openalex.org/W2994671176","https://openalex.org/W2996102538","https://openalex.org/W2997944991","https://openalex.org/W3014367186","https://openalex.org/W3016889634","https://openalex.org/W3034225195","https://openalex.org/W3034672970","https://openalex.org/W3034953156","https://openalex.org/W3035433720","https://openalex.org/W3081346573","https://openalex.org/W3085046840","https://openalex.org/W3108450508","https://openalex.org/W3124065089","https://openalex.org/W3127595489","https://openalex.org/W3129840128","https://openalex.org/W3132455321","https://openalex.org/W3169865585","https://openalex.org/W3175205795","https://openalex.org/W3175373394","https://openalex.org/W3196904463","https://openalex.org/W3203155465","https://openalex.org/W3217624019","https://openalex.org/W4200415850","https://openalex.org/W4225485763","https://openalex.org/W4283214228","https://openalex.org/W4287198652","https://openalex.org/W4287330664","https://openalex.org/W4293406525","https://openalex.org/W4300164464","https://openalex.org/W4308909683","https://openalex.org/W4386799137"],"related_works":["https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2080152487","https://openalex.org/W2239445980","https://openalex.org/W2995553446","https://openalex.org/W2055243143","https://openalex.org/W2120455979","https://openalex.org/W4200527723"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,19,73,82,115,118,130,146],"task":[4],"of":[5,22,132,148],"semantic":[6,25,29,63,142,152],"segmentation":[7,64,143],"in":[8,41,75,150],"computer":[9],"vision,":[10],"aiming":[11],"to":[12,109],"achieve":[13],"precise":[14],"pixel\u2010wise":[15],"classification.":[16],"We":[17],"investigate":[18],"joint":[20],"training":[21],"models":[23],"for":[24,140],"edge":[26],"detection":[27],"and":[28,135,144],"segmentation,":[30],"which":[31],"has":[32],"shown":[33],"a":[34,51,68],"promise.":[35],"However,":[36],"implicit":[37],"cross\u2010task":[38,54,60,137],"consistency":[39,55,138],"learning":[40,134],"multitask":[42,133],"networks":[43],"is":[44,106],"limited.":[45],"To":[46],"address":[47],"this,":[48],"we":[49],"propose":[50],"novel":[52],"\u201cdecoupled":[53],"loss\u201d":[56],"that":[57],"explicitly":[58],"enhances":[59],"consistency.":[61],"Our":[62],"network,":[65],"TriangleNet,":[66],"achieves":[67],"substantial":[69],"2.88%":[70],"improvement":[71],"over":[72,78],"Baseline":[74,116],"mean":[76],"Intersection":[77],"Union":[79],"(mIoU)":[80],"on":[81,93,117],"Cityscapes":[83],"test":[84],"set.":[85],"Notably,":[86],"TriangleNet":[87,112],"operates":[88],"at":[89,99],"77.4%":[90],"mIoU/46.2":[91],"FPS":[92],"Cityscapes,":[94],"showcasing":[95],"real\u2010time":[96,151],"inference":[97],"capabilities":[98],"full":[100],"resolution.":[101],"With":[102],"multiscale":[103],"inference,":[104],"performance":[105],"further":[107],"enhanced":[108],"77.8%.":[110],"Furthermore,":[111],"consistently":[113],"outperforms":[114],"FloodNet":[119],"dataset,":[120],"demonstrating":[121],"its":[122],"robust":[123],"generalization":[124],"capabilities.":[125],"The":[126],"proposed":[127],"method":[128],"underscores":[129],"significance":[131],"explicit":[136],"enhancement":[139],"advancing":[141],"highlights":[145],"potential":[147],"multitasking":[149],"segmentation.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
