{"id":"https://openalex.org/W4319786658","doi":"https://doi.org/10.3389/fnbot.2023.1119231","title":"Rethinking 1D convolution for lightweight semantic segmentation","display_name":"Rethinking 1D convolution for lightweight semantic segmentation","publication_year":2023,"publication_date":"2023-02-09","ids":{"openalex":"https://openalex.org/W4319786658","doi":"https://doi.org/10.3389/fnbot.2023.1119231","pmid":"https://pubmed.ncbi.nlm.nih.gov/36845064"},"language":"en","primary_location":{"id":"doi:10.3389/fnbot.2023.1119231","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fnbot.2023.1119231","pdf_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2023.1119231/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2023.1119231/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100439738","display_name":"Chunyu Zhang","orcid":"https://orcid.org/0000-0002-5682-1647"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunyu Zhang","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059069514","display_name":"Fang Xu","orcid":"https://orcid.org/0009-0001-1478-1704"},"institutions":[{"id":"https://openalex.org/I142078773","display_name":"Shenyang Institute of Automation","ror":"https://ror.org/00ft6nj33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I142078773","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Xu","raw_affiliation_strings":["Shenyang Siasun Robot & Automation Company Ltd., Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Siasun Robot & Automation Company Ltd., Shenyang, China","institution_ids":["https://openalex.org/I142078773"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000383993","display_name":"Chengdong Wu","orcid":"https://orcid.org/0000-0001-9906-5493"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengdong Wu","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053359294","display_name":"Chenglong Xu","orcid":"https://orcid.org/0009-0003-7058-6481"},"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":"Chenglong Xu","raw_affiliation_strings":["College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100439738"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":{"value":2950,"currency":"USD","value_usd":2950},"apc_paid":{"value":2950,"currency":"USD","value_usd":2950},"fwci":0.2127,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45373299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"17","issue":null,"first_page":"1119231","last_page":"1119231"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9954000115394592,"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":0.9947999715805054,"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":0.8478599786758423},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.668914258480072},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5809161067008972},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5651665925979614},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5314976572990417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49829745292663574},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49751046299934387},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4866698384284973},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43832048773765564},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4366898536682129},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.425296813249588},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG 2000","score":0.4153464436531067},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35997939109802246},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.21373692154884338},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.1356479525566101},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13511335849761963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8478599786758423},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.668914258480072},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5809161067008972},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5651665925979614},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5314976572990417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49829745292663574},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49751046299934387},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4866698384284973},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43832048773765564},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4366898536682129},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.425296813249588},{"id":"https://openalex.org/C69216139","wikidata":"https://www.wikidata.org/wiki/Q931783","display_name":"JPEG 2000","level":5,"score":0.4153464436531067},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35997939109802246},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.21373692154884338},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.1356479525566101},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13511335849761963},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fnbot.2023.1119231","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fnbot.2023.1119231","pdf_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2023.1119231/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},{"id":"pmid:36845064","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36845064","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":"Frontiers in neurorobotics","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9947531","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9947531","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9947531/pdf/fnbot-17-1119231.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Neurorobot","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:0abf946b232742ef8d0a27a44f877888","is_oa":true,"landing_page_url":"https://doaj.org/article/0abf946b232742ef8d0a27a44f877888","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Neurorobotics, Vol 17 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fnbot.2023.1119231","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fnbot.2023.1119231","pdf_url":"https://www.frontiersin.org/articles/10.3389/fnbot.2023.1119231/pdf","source":{"id":"https://openalex.org/S115606517","display_name":"Frontiers in Neurorobotics","issn_l":"1662-5218","issn":["1662-5218"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Neurorobotics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4319786658.pdf"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W1745334888","https://openalex.org/W1913356549","https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2340897893","https://openalex.org/W2560023338","https://openalex.org/W2735039185","https://openalex.org/W2762439315","https://openalex.org/W2883780447","https://openalex.org/W2884585870","https://openalex.org/W2886934227","https://openalex.org/W2907965334","https://openalex.org/W2910628332","https://openalex.org/W2921526792","https://openalex.org/W2955425717","https://openalex.org/W2962772649","https://openalex.org/W2963163009","https://openalex.org/W2963418739","https://openalex.org/W2963881378","https://openalex.org/W2963890956","https://openalex.org/W2964217532","https://openalex.org/W2964309882","https://openalex.org/W2965380104","https://openalex.org/W2970056511","https://openalex.org/W2971198903","https://openalex.org/W2982083293","https://openalex.org/W2996102538","https://openalex.org/W3015280606","https://openalex.org/W3034926724","https://openalex.org/W3094502228","https://openalex.org/W3105636206","https://openalex.org/W3106747537","https://openalex.org/W3110440461","https://openalex.org/W3112503277","https://openalex.org/W3133696297","https://openalex.org/W3139049060","https://openalex.org/W3156811085","https://openalex.org/W3158385340","https://openalex.org/W3169865585","https://openalex.org/W3170841864","https://openalex.org/W3172265425","https://openalex.org/W3196904463","https://openalex.org/W3211490618","https://openalex.org/W3212386989","https://openalex.org/W4206573688","https://openalex.org/W4206706211","https://openalex.org/W4213019189","https://openalex.org/W4213099919","https://openalex.org/W4226085666","https://openalex.org/W4285134614","https://openalex.org/W4292829030","https://openalex.org/W4293406525","https://openalex.org/W4385346076","https://openalex.org/W6695314431","https://openalex.org/W6717372056","https://openalex.org/W6760613829","https://openalex.org/W6762718338","https://openalex.org/W6766273390","https://openalex.org/W6783951977","https://openalex.org/W6790690058","https://openalex.org/W6792695861","https://openalex.org/W6794906783","https://openalex.org/W6797399245","https://openalex.org/W6799166919","https://openalex.org/W6811173682"],"related_works":["https://openalex.org/W2517104666","https://openalex.org/W2005437358","https://openalex.org/W2295021132","https://openalex.org/W2546942002","https://openalex.org/W4386303287","https://openalex.org/W2772780115","https://openalex.org/W1977222486","https://openalex.org/W2049538278","https://openalex.org/W2115092356","https://openalex.org/W3148519004"],"abstract_inverted_index":{"Lightweight":[0],"semantic":[1,7,15,118,289],"segmentation":[2,8,16,290,300,320],"promotes":[3],"the":[4,20,34,53,75,84,103,122,129,140,148,154,158,163,177,180,202,228,238,243,247,254,260,264,272,277,296,315,318],"application":[5,261],"of":[6,22,29,47,124,131,147,204,256,263,306],"in":[9],"tiny":[10],"devices.":[11,268],"The":[12,44,72,111,183,269,304],"existing":[13],"lightweight":[14,288],"network":[17,49,208,244,265,278,294,316],"(LSNet)":[18],"has":[19],"problems":[21],"low":[23],"precision":[24,125],"and":[25,67,74,116,157,195,212,224,231,234,253,302],"a":[26,39,135,197,215],"large":[27],"number":[28],"parameters.":[30,303,325],"In":[31],"response":[32],"to":[33,52,179,192,200,250,286],"above":[35],"problems,":[36],"we":[37,281],"designed":[38,134,282,293],"full":[40],"1D":[41,57,62,92],"convolutional":[42,93],"LSNet.":[43],"tremendous":[45],"success":[46],"this":[48],"is":[50,96,176,283,313],"attributed":[51],"following":[54],"three":[55,273],"modules:":[56],"multi-layer":[58,63,85],"space":[59,150],"module":[60,65,70,90,113,156,199],"(1D-MS),":[61],"channel":[64,159],"(1D-MC),":[66],"flow":[68],"alignment":[69],"(FA).":[71],"1D-MS":[73,155],"1D-MC":[76,164],"add":[77],"global":[78,104],"feature":[79,149,205],"extraction":[80],"operations":[81],"based":[82,138],"on":[83,139,227,237,246,266,271],"perceptron":[86],"(MLP)":[87],"idea.":[88],"This":[89],"uses":[91,189],"coding,":[94],"which":[95,120,175,312],"more":[97],"flexible":[98],"than":[99],"MLP.":[100],"It":[101,143,220],"increases":[102],"information":[105,151,160],"operation,":[106],"improving":[107],"features'":[108],"coding":[109],"ability.":[110],"FA":[112,187,198],"fuses":[114],"high-level":[115],"low-level":[117],"information,":[119],"solves":[121],"problem":[123,203],"loss":[126],"caused":[127],"by":[128,153,162],"misalignment":[130],"features.":[132],"We":[133,241],"1D-mixer":[136,166],"encoder":[137],"transformer":[141],"structure.":[142],"performed":[144],"fusion":[145],"encoding":[146],"extracted":[152,161],"module.":[165],"obtains":[167],"high-quality":[168],"encoded":[169],"features":[170,194],"with":[171,186,317],"very":[172],"few":[173],"parameters,":[174],"key":[178],"network's":[181],"success.":[182],"attention":[184],"pyramid":[185],"(AP-FA)":[188],"an":[190],"AP":[191],"decode":[193],"adds":[196],"solve":[201],"misalignment.":[206],"Our":[207],"requires":[209],"no":[210],"pre-training":[211],"only":[213,309],"needs":[214],"1080Ti":[216],"GPU":[217],"for":[218],"training.":[219],"achieved":[221],"72.6":[222],"mIoU":[223,233],"95.6":[225],"FPS":[226,236],"Cityscapes":[229],"dataset":[230,249],"70.5":[232],"122":[235],"CamVid":[239],"dataset.":[240],"ported":[242],"trained":[245],"ADE2K":[248],"mobile":[251,267],"devices,":[252],"latency":[255],"224":[257],"ms":[258],"proves":[259],"value":[262],"results":[270],"datasets":[274],"prove":[275],"that":[276],"generalization":[279],"ability":[280],"powerful.":[284],"Compared":[285],"state-of-the-art":[287],"algorithms,":[291],"our":[292],"achieves":[295],"best":[297],"balance":[298],"between":[299],"accuracy":[301,321],"parameters":[305],"LSNet":[307],"are":[308],"0.62":[310],"M,":[311],"currently":[314],"highest":[319],"within":[322],"1":[323],"M":[324]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
