{"id":"https://openalex.org/W3120691194","doi":"https://doi.org/10.1117/12.2586932","title":"Application of shared backbone DNNs in ADAS perception systems","display_name":"Application of shared backbone DNNs in ADAS perception systems","publication_year":2021,"publication_date":"2021-01-04","ids":{"openalex":"https://openalex.org/W3120691194","doi":"https://doi.org/10.1117/12.2586932","mag":"3120691194"},"language":"en","primary_location":{"id":"doi:10.1117/12.2586932","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2586932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Thirteenth International Conference on Machine Vision","raw_type":"proceedings-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/A5021172209","display_name":"Mikhail G. Lobanov","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116317","display_name":"Russian State Scientific Center for Robotics and Technical Cybernetics","ror":"https://ror.org/02dkph265","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210116317"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Mikhail G. Lobanov","raw_affiliation_strings":["Cognitive Robotics Ltd. (Russian Federation)"],"affiliations":[{"raw_affiliation_string":"Cognitive Robotics Ltd. (Russian Federation)","institution_ids":["https://openalex.org/I4210116317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007533053","display_name":"Dmitry L. Sholomov","orcid":"https://orcid.org/0000-0001-6011-0728"},"institutions":[{"id":"https://openalex.org/I4210107660","display_name":"Institute for Information Transmission Problems","ror":"https://ror.org/013w2d378","country_code":"RU","type":"facility","lineage":["https://openalex.org/I1313323035","https://openalex.org/I4210097085","https://openalex.org/I4210107660"]},{"id":"https://openalex.org/I12003341","display_name":"National University of Science and Technology","ror":"https://ror.org/019vsm959","country_code":"RU","type":"education","lineage":["https://openalex.org/I12003341"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Dmitry L. Sholomov","raw_affiliation_strings":["Institute for Information Transmission Problems, RAS (Russian Federation)","National Univ. of Science and Technology MISIS (Russian Federation)"],"affiliations":[{"raw_affiliation_string":"Institute for Information Transmission Problems, RAS (Russian Federation)","institution_ids":["https://openalex.org/I4210107660"]},{"raw_affiliation_string":"National Univ. of Science and Technology MISIS (Russian Federation)","institution_ids":["https://openalex.org/I12003341"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021172209"],"corresponding_institution_ids":["https://openalex.org/I4210116317"],"apc_list":null,"apc_paid":null,"fwci":0.6725,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.69797386,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"20","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9980999827384949,"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/computer-science","display_name":"Computer science","score":0.8663592338562012},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.8081238269805908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5841787457466125},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5790882706642151},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5769633054733276},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5623570084571838},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5525757670402527},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5258403420448303},{"id":"https://openalex.org/keywords/advanced-driver-assistance-systems","display_name":"Advanced driver assistance systems","score":0.4781666398048401},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46721234917640686},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45610907673835754},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4552253484725952},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45436009764671326},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4375406801700592},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.4328826367855072},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11280426383018494}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8663592338562012},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.8081238269805908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5841787457466125},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5790882706642151},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5769633054733276},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5623570084571838},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5525757670402527},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5258403420448303},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.4781666398048401},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46721234917640686},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45610907673835754},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4552253484725952},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45436009764671326},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4375406801700592},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.4328826367855072},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11280426383018494},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2586932","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2586932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Thirteenth International Conference on Machine Vision","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2190968165","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2601564443","https://openalex.org/W2772801996","https://openalex.org/W2799352588","https://openalex.org/W2800516981","https://openalex.org/W2886934227","https://openalex.org/W2964217532","https://openalex.org/W2972211064","https://openalex.org/W2981857055","https://openalex.org/W3003225268","https://openalex.org/W3099319035"],"related_works":["https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W1966421350","https://openalex.org/W1868434454","https://openalex.org/W4366985237","https://openalex.org/W2894651257","https://openalex.org/W3200590620","https://openalex.org/W4200172193","https://openalex.org/W4303926741"],"abstract_inverted_index":{"Advanced":[0],"Driver":[1],"Assistance":[2],"System":[3],"(ADAS)":[4],"is":[5,56,104,129,173,189,226],"a":[6,127,130,151,163,190],"very":[7],"important":[8],"part":[9],"of":[10,40,72,115,120,143,176,211,251],"an":[11],"up":[12],"to":[13,69,112,124,228,269],"date":[14],"vehicle.":[15],"For":[16],"achieving":[17],"highlevel":[18],"objectives":[19],"in":[20,279],"such":[21,126,212],"ADAS":[22],"functionality":[23],"like":[24],"LKA":[25],"(lane":[26,30],"keeping":[27],"assistance),":[28],"LDW":[29],"departure":[31],"warning":[32],"system),":[33],"FCW":[34],"(forward":[35],"collision":[36],"warning)":[37],"the":[38,41,44,51,70,96,113,116,121,144,148,159,174,180,209,229,236,249,252,261,270],"quality":[39,262],"algorithms":[42,60],"under":[43],"hood":[45],"must":[46],"be":[47],"extremely":[48],"high.":[49],"In":[50,195],"last":[52],"few":[53],"years,":[54],"it":[55],"common":[57],"that":[58],"these":[59],"are":[61,266],"based":[62],"on":[63,215,235],"DNNs":[64,253,274],"(deep":[65],"neural":[66,102,204],"networks)":[67],"applied":[68,227],"tasks":[71,232],"semantic":[73,239],"and":[74,80,99,108,182,207,244,275],"instance":[75],"segmentation,":[76,240],"2D/3D":[77],"object":[78,82,242,246],"detection":[79,243],"visual":[81],"tracking.":[83],"Recent":[84],"state-of-the-art":[85,273],"DNN":[86],"models":[87],"as":[88],"usual":[89],"solve":[90],"only":[91],"one":[92,172],"single":[93],"task":[94],"from":[95],"listed":[97],"above":[98],"running":[100],"several":[101,168,200,216],"networks":[103],"rather":[105],"computationally":[106],"expensive":[107],"even":[109,276],"impossible":[110],"due":[111],"lack":[114,175],"GPU":[117],"memory.":[118],"One":[119],"approaches":[122],"used":[123],"overcome":[125],"problem":[128,188],"shared":[131,152,164,224,255],"backbone":[132,140,153,165,225,256],"(also":[133],"called":[134],"feature":[135],"extractor":[136],"or":[137],"encoder).":[138],"The":[139,170,186,223],"consumes":[141],"most":[142],"computing":[145],"resources":[146],"thus":[147],"model":[149,166],"with":[150,178,219,254],"achieves":[154],"better":[155],"inference":[156],"performance.":[157],"Unfortunately,":[158],"training":[160,206,213],"procedure":[161],"for":[162,202],"has":[167],"difficulties.":[169],"first":[171],"datasets":[177,218],"all":[179],"required":[181],"uniform":[183],"annotation":[184,221],"types.":[185,222],"second":[187],"more":[191],"sophisticated":[192],"backpropagation":[193],"procedure.":[194],"this":[196],"paper,":[197],"we":[198,259],"consider":[199],"methods":[201],"multi-task":[203],"network":[205],"present":[208],"results":[210],"procedures":[214],"public":[217],"dissimilar":[220],"following":[230],"three":[231],"performed":[233],"simultaneously":[234],"road":[237],"scene:":[238],"2D":[241],"3D":[245],"detection.":[247],"While":[248],"performance":[250],"increased":[257],"significantly,":[258],"obtained":[260],"evaluation":[263,281],"results,":[264],"which":[265],"quite":[267],"close":[268],"original":[271],"separate":[272],"outperforms":[277],"them":[278],"some":[280],"indices.":[282]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
