{"id":"https://openalex.org/W2976783011","doi":"https://doi.org/10.1109/iv47402.2020.9304548","title":"Towards Robust Direct Perception Networks for Automated Driving","display_name":"Towards Robust Direct Perception Networks for Automated Driving","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W2976783011","doi":"https://doi.org/10.1109/iv47402.2020.9304548","mag":"2976783011"},"language":"en","primary_location":{"id":"doi:10.1109/iv47402.2020.9304548","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv47402.2020.9304548","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1909.13600","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066292729","display_name":"Chih\u2010Hong Cheng","orcid":"https://orcid.org/0000-0002-7265-8413"},"institutions":[{"id":"https://openalex.org/I67530263","display_name":"Denso (United States)","ror":"https://ror.org/02w314k38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132650","https://openalex.org/I67530263"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chih-Hong Cheng","raw_affiliation_strings":["Corporate R&D, DENSO AUTOMOTIVE Deutschland GmbH"],"affiliations":[{"raw_affiliation_string":"Corporate R&D, DENSO AUTOMOTIVE Deutschland GmbH","institution_ids":["https://openalex.org/I67530263"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5066292729"],"corresponding_institution_ids":["https://openalex.org/I67530263"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0070776,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"298","last_page":"304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9930999875068665,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9865000247955322,"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/bounded-function","display_name":"Bounded function","score":0.6200841069221497},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5944965481758118},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.564695417881012},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5168538689613342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5081932544708252},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4970112144947052},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.4591365158557892},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4532736837863922},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.426929771900177},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4173327088356018},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36029869318008423},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2971963882446289},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.19450122117996216},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1853194534778595},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16596809029579163}],"concepts":[{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.6200841069221497},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5944965481758118},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.564695417881012},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5168538689613342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5081932544708252},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4970112144947052},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.4591365158557892},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4532736837863922},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.426929771900177},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4173327088356018},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36029869318008423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2971963882446289},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.19450122117996216},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1853194534778595},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16596809029579163},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iv47402.2020.9304548","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv47402.2020.9304548","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1909.13600","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1909.13600","pdf_url":"https://arxiv.org/pdf/1909.13600","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2976783011","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1909.13600","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1909.13600","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1909.13600","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1909.13600","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1909.13600","pdf_url":"https://arxiv.org/pdf/1909.13600","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2976783011.pdf","grobid_xml":"https://content.openalex.org/works/W2976783011.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1665214252","https://openalex.org/W2043100293","https://openalex.org/W2119112357","https://openalex.org/W2165073069","https://openalex.org/W2167224731","https://openalex.org/W2543296129","https://openalex.org/W2594877703","https://openalex.org/W2616028256","https://openalex.org/W2721006554","https://openalex.org/W2766462876","https://openalex.org/W2789524546","https://openalex.org/W2791251367","https://openalex.org/W2793633339","https://openalex.org/W2794609696","https://openalex.org/W2800473699","https://openalex.org/W2801079363","https://openalex.org/W2801779715","https://openalex.org/W2804452021","https://openalex.org/W2899692219","https://openalex.org/W2917325587","https://openalex.org/W2953707919","https://openalex.org/W2962700793","https://openalex.org/W2962943487","https://openalex.org/W2963054787","https://openalex.org/W2963285578","https://openalex.org/W2963440492","https://openalex.org/W2963496101","https://openalex.org/W2963539647","https://openalex.org/W2963556353","https://openalex.org/W2963600714","https://openalex.org/W2963626025","https://openalex.org/W2963673089","https://openalex.org/W2963727600","https://openalex.org/W2963735478","https://openalex.org/W2963913218","https://openalex.org/W2964153729","https://openalex.org/W2971109239","https://openalex.org/W2980176926","https://openalex.org/W2981639301","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637162671","https://openalex.org/W6637242042","https://openalex.org/W6684338915","https://openalex.org/W6685562342","https://openalex.org/W6729243212","https://openalex.org/W6740406300","https://openalex.org/W6744680123","https://openalex.org/W6745454490","https://openalex.org/W6748093715","https://openalex.org/W6748277150","https://openalex.org/W6750745550","https://openalex.org/W6751044371","https://openalex.org/W6751161574","https://openalex.org/W6752034395","https://openalex.org/W6752781648","https://openalex.org/W6755693443","https://openalex.org/W6764522968","https://openalex.org/W6765694979"],"related_works":["https://openalex.org/W3127026589","https://openalex.org/W3175111689","https://openalex.org/W3002468741","https://openalex.org/W42834495","https://openalex.org/W3006340941","https://openalex.org/W2070566552","https://openalex.org/W3090244698","https://openalex.org/W2168790308","https://openalex.org/W3090779233","https://openalex.org/W958421984","https://openalex.org/W2737551986","https://openalex.org/W2770120020","https://openalex.org/W3037488448","https://openalex.org/W5187712","https://openalex.org/W2232492360","https://openalex.org/W2169584374","https://openalex.org/W2909904991","https://openalex.org/W3018938210","https://openalex.org/W1757919228","https://openalex.org/W2037737135"],"abstract_inverted_index":{"We":[0,113],"consider":[1],"the":[2,12,30,33,38,41,56,78,89,97,106,116,130,135,144,151,162,171,177,180,184,201,205],"problem":[3],"of":[4,32,63,91,204],"engineering":[5,193],"robust":[6,124,152],"direct":[7,195],"perception":[8,196],"neural":[9,50,197],"networks":[10,17],"with":[11,58,81],"output":[13,132,172],"being":[14],"regression.":[15],"Such":[16],"take":[18],"high":[19],"dimensional":[20],"input":[21],"image":[22],"data,":[23],"and":[24,119,143,183],"they":[25],"produce":[26],"affordances":[27],"such":[28],"as":[29,105],"curvature":[31],"upcoming":[34],"road":[35],"segment":[36],"or":[37,69],"distance":[39,108],"to":[40,53,101,129,170],"front":[42],"vehicle.":[43],"Our":[44],"proposal":[45],"starts":[46],"by":[47,156,168,175],"allowing":[48],"a":[49,92,121,194],"network":[51,198],"prediction":[52],"deviate":[54],"from":[55,70,161],"label":[57,77],"tolerance":[59,64,87,133],"\u0394.":[60,112],"The":[61,86,187],"source":[62],"can":[65],"be":[66],"either":[67],"contractual":[68],"limiting":[71],"factors":[72],"where":[73,96,139],"two":[74],"entities":[75],"may":[76],"same":[79],"data":[80],"slightly":[82],"different":[83],"numerical":[84],"values.":[85],"motivates":[88],"use":[90],"non-standard":[93],"loss":[94,98,117,153],"function":[95,118],"is":[99,109,127,141,154,190],"set":[100],"0":[102],"so":[103],"long":[104],"prediction-to-label":[107],"less":[110],"than":[111],"further":[114],"extend":[115],"define":[120],"new":[122],"provably":[123],"criterion":[125],"that":[126],"parametric":[128],"allowed":[131,185],"\u0394,":[134],"layer":[136,164],"index":[137],"l":[138],"perturbation":[140,146],"considered,":[142],"maximum":[145],"amount":[147],"\u03ba.":[148],"During":[149],"training,":[150],"computed":[155],"first":[157],"propagating":[158],"symbolic":[159],"errors":[160],"l\u0303-th":[163],"(with":[165],"quantity":[166],"bounded":[167],"\u03ba)":[169],"layer,":[173],"followed":[174],"computing":[176],"overflow":[178],"between":[179],"error":[181],"bounds":[182],"tolerance.":[186],"overall":[188],"concept":[189],"experimented":[191],"in":[192,207],"for":[199],"understanding":[200],"central":[202],"position":[203],"ego-lane":[206],"pixel":[208],"coordinates.":[209]},"counts_by_year":[],"updated_date":"2026-02-24T19:35:01.260952","created_date":"2025-10-10T00:00:00"}