{"id":"https://openalex.org/W4415968682","doi":"https://doi.org/10.1109/iecon58223.2025.11221461","title":"Enhanced Drift-Aware Computer Vision Architecture for Autonomous Driving","display_name":"Enhanced Drift-Aware Computer Vision Architecture for Autonomous Driving","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W4415968682","doi":"https://doi.org/10.1109/iecon58223.2025.11221461"},"language":null,"primary_location":{"id":"doi:10.1109/iecon58223.2025.11221461","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","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/A5111353230","display_name":"Md Shahi Amran Hossain","orcid":null},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Md Shahi Amran Hossain","raw_affiliation_strings":["University of Siegen,Chair of Embedded Systems,Siegen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Siegen,Chair of Embedded Systems,Siegen,Germany","institution_ids":["https://openalex.org/I206895457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049953469","display_name":"Abu Shad Ahammed","orcid":"https://orcid.org/0009-0007-6715-8098"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Abu Shad Ahammed","raw_affiliation_strings":["University of Siegen,Chair of Embedded Systems,Siegen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Siegen,Chair of Embedded Systems,Siegen,Germany","institution_ids":["https://openalex.org/I206895457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113051582","display_name":"S. Mukherjee","orcid":"https://orcid.org/0000-0003-4906-2264"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sayeri Mukherjee","raw_affiliation_strings":["University of Siegen,Chair of Embedded Systems,Siegen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Siegen,Chair of Embedded Systems,Siegen,Germany","institution_ids":["https://openalex.org/I206895457"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007015294","display_name":"Roman Obermaisser","orcid":"https://orcid.org/0009-0002-4483-1503"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Roman Obermaisser","raw_affiliation_strings":["University of Siegen,Chair of Embedded Systems,Siegen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Siegen,Chair of Embedded Systems,Siegen,Germany","institution_ids":["https://openalex.org/I206895457"]}]}],"institutions":[],"countries_distinct_count":1,"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":0.28476932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6032999753952026,"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":0.6032999753952026,"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":0.15279999375343323,"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/T11019","display_name":"Image Enhancement Techniques","score":0.05689999833703041,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5920000076293945},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5612000226974487},{"id":"https://openalex.org/keywords/standardization","display_name":"Standardization","score":0.5246000289916992},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5019000172615051},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.420199990272522},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.39660000801086426}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5920000076293945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5703999996185303},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5612000226974487},{"id":"https://openalex.org/C188087704","wikidata":"https://www.wikidata.org/wiki/Q369577","display_name":"Standardization","level":2,"score":0.5246000289916992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.510699987411499},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5019000172615051},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.39660000801086426},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.3898000121116638},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3720000088214874},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.33410000801086426},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2818000018596649},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.27559998631477356},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.2623000144958496}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon58223.2025.11221461","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2576845151","https://openalex.org/W2963037989","https://openalex.org/W3034269714","https://openalex.org/W3041519490","https://openalex.org/W3044201829","https://openalex.org/W3093113420","https://openalex.org/W3117590843","https://openalex.org/W3199222072","https://openalex.org/W4200101657","https://openalex.org/W4221041279","https://openalex.org/W4226217181","https://openalex.org/W4297838791","https://openalex.org/W4382004600","https://openalex.org/W4390176587","https://openalex.org/W4399449138","https://openalex.org/W4403125772","https://openalex.org/W4405446156","https://openalex.org/W4408456033","https://openalex.org/W4408703525","https://openalex.org/W4408703542"],"related_works":[],"abstract_inverted_index":{"The":[0,130,150],"use":[1],"of":[2,97],"computer":[3,91],"vision":[4,92],"in":[5,11,108,133,168],"automotive":[6],"is":[7],"a":[8,17,88,125,157,169],"trending":[9],"research":[10],"which":[12],"safety":[13,81,164],"and":[14,79,123,135],"security":[15],"are":[16],"primary":[18],"concern.":[19],"In":[20,83],"particular,":[21],"for":[22,44,54,120,128],"autonomous":[23],"driving,":[24],"preventing":[25],"road":[26,103,148,163],"accidents":[27],"requires":[28],"highly":[29],"accurate":[30],"object":[31],"detection":[32,122,138],"under":[33],"diverse":[34],"conditions.":[35],"To":[36],"address":[37],"this":[38,84],"issue,":[39],"recently":[40],"the":[41,48,102,137],"International":[42],"Organization":[43],"Standardization":[45],"(ISO)":[46],"released":[47],"8800":[49],"norm,":[50],"providing":[51],"structured":[52],"frameworks":[53],"managing":[55],"associated":[56],"AI":[57],"relevant":[58],"risks.":[59],"However,":[60],"challenging":[61],"scenarios":[62],"such":[63,156],"as":[64],"adverse":[65],"weather":[66],"or":[67],"low":[68],"lighting":[69],"often":[70],"introduce":[71],"data":[72,100],"drift,":[73],"leading":[74],"to":[75,105,153],"degraded":[76],"model":[77,159],"performance":[78],"potential":[80],"violations.":[82],"work,":[85],"we":[86],"present":[87],"novel":[89],"hybrid":[90,158,170],"architecture":[93],"trained":[94],"with":[95,146],"thousands":[96],"synthetic":[98],"image":[99],"from":[101],"environment":[104],"improve":[106],"robustness":[107],"unseen":[109],"drifted":[110],"environments.":[111],"Our":[112],"dual":[113],"mode":[114],"framework":[115],"utilized":[116],"YOLO":[117],"version":[118],"8":[119],"swift":[121],"incorporated":[124],"five-layer":[126],"CNN":[127],"verification.":[129],"system":[131],"functioned":[132],"sequence":[134],"improved":[136],"accuracy":[139],"by":[140],"more":[141],"than":[142],"90%":[143],"when":[144,165],"tested":[145],"drift-augmented":[147],"images.":[149],"focus":[151],"was":[152],"demonstrate":[154],"how":[155],"can":[160],"provide":[161],"better":[162],"working":[166],"together":[167],"structure.":[171]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-06T00:00:00"}