{"id":"https://openalex.org/W3122625936","doi":"https://doi.org/10.1109/lsp.2021.3051845","title":"EACNet: Enhanced Asymmetric Convolution for Real-Time Semantic Segmentation","display_name":"EACNet: Enhanced Asymmetric Convolution for Real-Time Semantic Segmentation","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3122625936","doi":"https://doi.org/10.1109/lsp.2021.3051845","mag":"3122625936"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2021.3051845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3051845","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","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/A5100697596","display_name":"Yaqian Li","orcid":"https://orcid.org/0000-0002-3541-2836"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaqian Li","raw_affiliation_strings":["Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0002-3541-2836","affiliations":[{"raw_affiliation_string":"Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100628719","display_name":"Xiaokun Li","orcid":"https://orcid.org/0000-0002-1118-1025"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaokun Li","raw_affiliation_strings":["Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China"],"raw_orcid":"https://orcid.org/0000-0002-1118-1025","affiliations":[{"raw_affiliation_string":"Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053766820","display_name":"Cunjun Xiao","orcid":"https://orcid.org/0000-0001-5348-3147"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cunjun Xiao","raw_affiliation_strings":["Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101812334","display_name":"Haibin Li","orcid":"https://orcid.org/0000-0002-0310-2892"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibin Li","raw_affiliation_strings":["Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100761291","display_name":"Wenming Zhang","orcid":"https://orcid.org/0000-0003-3802-3534"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Zhang","raw_affiliation_strings":["Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39333907"],"apc_list":null,"apc_paid":null,"fwci":3.2034,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.9330389,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"28","issue":null,"first_page":"234","last_page":"238"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9987999796867371,"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":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.8266716003417969},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7967549562454224},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7760188579559326},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6204655170440674},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5458170175552368},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5311673283576965},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5101504921913147},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49173691868782043},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3693612813949585},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3534301817417145},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34711945056915283}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.8266716003417969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7967549562454224},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7760188579559326},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6204655170440674},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5458170175552368},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5311673283576965},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5101504921913147},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49173691868782043},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3693612813949585},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3534301817417145},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34711945056915283},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2021.3051845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3051845","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W2119144962","https://openalex.org/W2340897893","https://openalex.org/W2419448466","https://openalex.org/W2560023338","https://openalex.org/W2762439315","https://openalex.org/W2775208825","https://openalex.org/W2886934227","https://openalex.org/W2901189993","https://openalex.org/W2921526792","https://openalex.org/W2963418739","https://openalex.org/W2963881378","https://openalex.org/W2963890956","https://openalex.org/W2964217532","https://openalex.org/W2964299589","https://openalex.org/W2964309882","https://openalex.org/W2965380104","https://openalex.org/W2971198903","https://openalex.org/W2973465872","https://openalex.org/W2981609437","https://openalex.org/W2988668960","https://openalex.org/W3011933327","https://openalex.org/W3014795891","https://openalex.org/W3021040258","https://openalex.org/W3023158620","https://openalex.org/W3034870355","https://openalex.org/W3034926724","https://openalex.org/W3112503277","https://openalex.org/W3196904463","https://openalex.org/W4293406525","https://openalex.org/W4297775537","https://openalex.org/W6638667902","https://openalex.org/W6677580257","https://openalex.org/W6717372056","https://openalex.org/W6737324727","https://openalex.org/W6737664043","https://openalex.org/W6746954591","https://openalex.org/W6748481559","https://openalex.org/W6749046737","https://openalex.org/W6756319154","https://openalex.org/W6766273390","https://openalex.org/W6767537170","https://openalex.org/W6768868819","https://openalex.org/W6776044926","https://openalex.org/W6779427727"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2964954556","https://openalex.org/W2890372105","https://openalex.org/W3019910406","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Although":[0],"deep":[1],"neural":[2],"networks":[3],"have":[4],"made":[5],"significant":[6],"progress":[7],"in":[8,78],"semantic":[9,89,136],"segmentation,":[10],"speed":[11,127],"and":[12,41,58,64,70,126,148],"computational":[13],"cost":[14],"still":[15],"can't":[16],"meet":[17],"the":[18,80,88,104,116],"strict":[19],"requirements":[20],"of":[21,48,103],"real-world":[22],"applications.":[23],"In":[24],"this":[25],"paper,":[26],"we":[27,44,73],"present":[28],"an":[29],"enhanced":[30],"asymmetric":[31,50,56],"convolution":[32,51,57,60],"network":[33,105,140],"(EACNet)":[34],"to":[35,61,106],"seek":[36],"a":[37,46,75,142],"balance":[38],"between":[39,110],"accuracy":[40,125],"speed.":[42],"Specifically,":[43],"design":[45],"pair":[47],"enhancing":[49],"modules":[52],"constructed":[53],"by":[54],"depth-wise":[55],"dilated":[59],"extract":[62],"short-range":[63],"long-range":[65],"features,":[66],"which":[67,79],"are":[68,98],"efficient":[69],"powerful.":[71],"Additionally,":[72],"apply":[74],"bilateral":[76],"structure":[77],"detail":[81],"branch":[82,90],"preserves":[83],"low-level":[84],"spatial":[85],"details":[86],"while":[87],"captures":[91],"high-level":[92],"context":[93],"information.":[94],"The":[95,113],"two":[96],"branches":[97],"merged":[99],"at":[100],"different":[101,111],"stages":[102],"strengthen":[107],"information":[108],"propagation":[109],"levels.":[112],"experiments":[114],"on":[115],"Cityscapes":[117],"dataset":[118],"show":[119],"that":[120],"our":[121,139],"method":[122],"achieves":[123],"high":[124],"with":[128,133],"relatively":[129],"small":[130],"parameters.":[131],"Compared":[132],"other":[134],"real-time":[135],"segmentation":[137],"methods,":[138],"attains":[141],"good":[143],"trade-off":[144],"among":[145],"parameters,":[146],"speed,":[147],"accuracy.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
