{"id":"https://openalex.org/W6959748629","doi":"https://doi.org/10.1145/3606042.3616451","title":"A Scalable Real-time Semantic Segmentation Network for Autonomous Driving","display_name":"A Scalable Real-time Semantic Segmentation Network for Autonomous Driving","publication_year":2023,"publication_date":"2023-10-29","ids":{"openalex":"https://openalex.org/W6959748629","doi":"https://doi.org/10.1145/3606042.3616451"},"language":"en","primary_location":{"id":"pmh:oai:digitalcommons.mtu.edu:michigantech-p2-1317","is_oa":false,"landing_page_url":"https://digitalcommons.mtu.edu/michigantech-p2/318","pdf_url":null,"source":{"id":"https://openalex.org/S4377196391","display_name":"Digital Commons - Michigan Tech (Michigan Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11957088","host_organization_name":"Michigan Technological University","host_organization_lineage":["https://openalex.org/I11957088"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Michigan Tech Publications","raw_type":"text"},"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Liu, Jun","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liu, Jun","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wu, Chao","orcid":null},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Wu, Chao","raw_affiliation_strings":["Northeastern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuan, Geng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Geng","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Niu, Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Wei","raw_affiliation_strings":["University of Georgia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhang, Wenbin","orcid":null},"institutions":[{"id":"https://openalex.org/I11957088","display_name":"Michigan Technological University","ror":"https://ror.org/0036rpn28","country_code":"US","type":"education","lineage":["https://openalex.org/I11957088"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhang, Wenbin","raw_affiliation_strings":["Michigan Technological University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan Technological University","institution_ids":["https://openalex.org/I11957088"]}]},{"author_position":"last","author":{"id":null,"display_name":"Song, Houbing Herbert","orcid":null},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song, Houbing Herbert","raw_affiliation_strings":["University of Maryland, Baltimore County (UMBC)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, Baltimore County (UMBC)","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59220295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12771","display_name":"Plant pathogens and resistance mechanisms","score":0.2732999920845032,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12771","display_name":"Plant pathogens and resistance mechanisms","score":0.2732999920845032,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13125","display_name":"Agricultural pest management studies","score":0.1096000000834465,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13506","display_name":"Botanical Research and Chemistry","score":0.09279999881982803,"subfield":{"id":"https://openalex.org/subfields/1105","display_name":"Ecology, Evolution, Behavior and Systematics"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.6347000002861023},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5475000143051147},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5311999917030334},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5145999789237976},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.487199991941452},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4749000072479248},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4530999958515167},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44429999589920044},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43479999899864197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7718999981880188},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.6347000002861023},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5475000143051147},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5311999917030334},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5145999789237976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5108000040054321},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4749000072479248},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4530999958515167},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44429999589920044},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43479999899864197},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.3822000026702881},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3343000113964081},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C127964446","wikidata":"https://www.wikidata.org/wiki/Q1092142","display_name":"Computational resource","level":3,"score":0.32899999618530273},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.321399986743927},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31060001254081726},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.30709999799728394},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2565999925136566},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2531000077724457}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:digitalcommons.mtu.edu:michigantech-p2-1317","is_oa":false,"landing_page_url":"https://digitalcommons.mtu.edu/michigantech-p2/318","pdf_url":null,"source":{"id":"https://openalex.org/S4377196391","display_name":"Digital Commons - Michigan Tech (Michigan Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11957088","host_organization_name":"Michigan Technological University","host_organization_lineage":["https://openalex.org/I11957088"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Michigan Tech Publications","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Computational":[0],"resources":[1],"are":[2,254],"limited":[3],"on":[4,15,29],"real-time":[5],"embedded":[6],"devices,":[7],"so":[8],"the":[9,16,30,45,61,66,70,108,111,118,143,148,152,208,215,233,237,244,247],"available":[10],"computing":[11],"cost":[12],"of":[13,39,63,133,182,188,210,219,246],"deployment":[14],"target":[17],"platform":[18],"must":[19],"be":[20,35],"considered.":[21],"We":[22],"develop":[23],"a":[24,102,129],"feature":[25,119,139,145],"extraction":[26,120,140,146],"module":[27,91,121,141,150],"based":[28],"MobileNet":[31],"backbone":[32],"that":[33],"can":[34,127],"adjusted":[36],"in":[37,180,236],"terms":[38,181],"computational":[40,74,193],"complexity":[41],"and":[42,51,73,101,147,159,171,190,217,243,265],"capacity":[43,72,264],"using":[44],"depth":[46,231,245],"multiplier":[47],"parameter,":[48],"classifier":[49],"depth,":[50],"kernel":[52,234],"depth.":[53],"These":[54,252],"three":[55],"parameters":[56],"allow":[57],"us":[58],"to":[59,110,162,213,256],"control":[60],"count":[62],"channels":[64],"within":[65],"network,":[67],"effectively":[68],"managing":[69],"model's":[71],"requirements.":[75],"To":[76],"achieve":[77],"semantic":[78,135],"segmentation,":[79],"we":[80,126],"incorporate":[81],"additional":[82],"components,":[83],"such":[84],"as":[85,195],"an":[86],"extension":[87,90,124,149],"module.":[88],"This":[89],"typically":[92],"includes":[93],"1x1":[94],"pointwise":[95],"convolutional":[96,104],"layers":[97],"for":[98,106,155],"pixel-level":[99],"classification":[100,158],"transposed":[103],"layer":[105],"upsampling":[107],"output":[109],"original":[112],"input":[113],"image":[114],"size.":[115],"By":[116],"combining":[117],"with":[122],"this":[123,224],"module,":[125],"create":[128],"complete":[130],"architecture":[131],"capable":[132],"performing":[134],"segmentation":[136],"tasks.":[137],"The":[138],"provides":[142],"initial":[144],"adds":[151],"necessary":[153],"components":[154],"accurate":[156],"pixel-wise":[157],"upsampling.":[160],"Compared":[161],"Hardware-aware":[163],"Neural":[164],"Architecture":[165],"Search":[166],"(NAS),":[167],"pruning,":[168,170],"runtime":[169],"knowledge":[172],"distillation":[173],"methods,":[174],"our":[175],"model":[176],"has":[177],"several":[178],"advantages":[179],"modular":[183],"design,":[184],"structural":[185],"controllability,":[186],"ease":[187],"implementation,":[189],"cost-effectiveness.":[191],"Our":[192,202],"efficiency,":[194],"measured":[196],"by":[197,206],"FLOPS,":[198],"is":[199,204],"highly":[200],"competitive.":[201],"method":[203],"distinguished":[205],"solving":[207],"problem":[209],"MobileNet's":[211,230],"inability":[212],"adjust":[214],"size":[216,235],"number":[218],"convolution":[220],"kernels.":[221],"It":[222],"achieves":[223],"through":[225],"adaptable":[226],"parameter":[227],"tuning,":[228],"including":[229],"multiplier,":[232],"FCN":[238],"head's":[239],"Separable":[240],"Convolution":[241,250],"layer,":[242],"first":[248],"Point-wise":[249],"layer.":[251],"adjustments":[253],"customized":[255],"match":[257],"hardware's":[258],"max":[259],"multiply-accumulates":[260],"(MACs),":[261],"optimizing":[262],"network":[263],"maximizing":[266],"resource":[267],"utilization.":[268]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}