{"id":"https://openalex.org/W3090266837","doi":"https://doi.org/10.1109/icip40778.2020.9191046","title":"Radar + RGB Fusion For Robust Object Detection In Autonomous Vehicle","display_name":"Radar + RGB Fusion For Robust Object Detection In Autonomous Vehicle","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3090266837","doi":"https://doi.org/10.1109/icip40778.2020.9191046","mag":"3090266837"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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/A5040606113","display_name":"Ritu Yadav","orcid":"https://orcid.org/0000-0003-3599-3164"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ritu Yadav","raw_affiliation_strings":["Robotics Research Lab, Technische Universit\u00e4t, Kaiserslautern, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Research Lab, Technische Universit\u00e4t, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I153267046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087588602","display_name":"Axel Vierling","orcid":"https://orcid.org/0000-0002-8984-3797"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Axel Vierling","raw_affiliation_strings":["Robotics Research Lab, Technische Universit\u00e4t, Kaiserslautern, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Research Lab, Technische Universit\u00e4t, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I153267046"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027711778","display_name":"Karsten Berns","orcid":"https://orcid.org/0000-0002-9080-1404"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Karsten Berns","raw_affiliation_strings":["Robotics Research Lab, Technische Universit\u00e4t, Kaiserslautern, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics Research Lab, Technische Universit\u00e4t, Kaiserslautern, Germany","institution_ids":["https://openalex.org/I153267046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I153267046"],"apc_list":null,"apc_paid":null,"fwci":2.3494,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.90614089,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1986","last_page":"1990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.6922410726547241},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6681045889854431},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6177963614463806},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5910855531692505},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5519864559173584},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5359901189804077},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5264999270439148},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5056946277618408},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.48027992248535156},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.44603070616722107},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.43096548318862915},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.42721492052078247},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3416234850883484},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19017192721366882},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11748683452606201},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07093027234077454}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6922410726547241},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6681045889854431},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6177963614463806},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5910855531692505},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5519864559173584},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5359901189804077},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5264999270439148},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5056946277618408},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.48027992248535156},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.44603070616722107},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.43096548318862915},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.42721492052078247},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3416234850883484},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19017192721366882},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11748683452606201},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07093027234077454},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191046","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191046","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2046335673","https://openalex.org/W2134963432","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2566954145","https://openalex.org/W2613718673","https://openalex.org/W2741151098","https://openalex.org/W2888252458","https://openalex.org/W2943515156","https://openalex.org/W2963150697","https://openalex.org/W2963179609","https://openalex.org/W2963549237","https://openalex.org/W2963794428","https://openalex.org/W2970287838","https://openalex.org/W2972561078","https://openalex.org/W2986097283","https://openalex.org/W2989940015","https://openalex.org/W2995549977","https://openalex.org/W3016223102","https://openalex.org/W3035574168","https://openalex.org/W3103179390","https://openalex.org/W6620707391","https://openalex.org/W6639102338","https://openalex.org/W6757868134","https://openalex.org/W6760782946","https://openalex.org/W6767892146","https://openalex.org/W6771471907"],"related_works":["https://openalex.org/W2283162247","https://openalex.org/W4212983513","https://openalex.org/W2524507886","https://openalex.org/W2546942002","https://openalex.org/W4255402425","https://openalex.org/W4320802741","https://openalex.org/W4381734600","https://openalex.org/W4281689716","https://openalex.org/W3138960644","https://openalex.org/W2905303874"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"two":[3],"variations":[4],"of":[5,97],"architecture":[6,15],"referred":[7],"to":[8,17,27,65,74,128],"as":[9,44],"RANet":[10,107,125],"and":[11,40,48,124],"BIRANet.":[12],"The":[13],"proposed":[14,73],"aims":[16],"use":[18],"radar":[19,51,61],"signal":[20],"data":[21],"along":[22],"with":[23,102],"RGB":[24],"camera":[25],"images":[26],"form":[28],"a":[29,70],"robust":[30,130],"detection":[31],"network":[32,78,100],"that":[33],"works":[34],"efficiently,":[35],"even":[36],"in":[37,55],"variable":[38],"lighting":[39],"weather":[41],"conditions":[42],"such":[43],"rain,":[45],"dust,":[46],"fog,":[47],"others.":[49],"First,":[50],"information":[52],"is":[53,72,92,117],"fused":[54],"the":[56,87,95,113,132],"feature":[57],"extractor":[58],"network.":[59],"Second,":[60],"points":[62],"are":[63,126],"used":[64],"generate":[66],"guided":[67],"anchors.":[68],"Third,":[69],"method":[71],"improve":[75],"region":[76],"proposal":[77],"[1]":[79],"targets.":[80],"BIRANet":[81,123],"yields":[82],"72.3/75.3%":[83],"average":[84,110],"AP/AR":[85,111],"on":[86,112],"NuScenes":[88],"[2]":[89],"dataset,":[90,115],"which":[91,116],"better":[93],"than":[94],"performance":[96],"our":[98],"base":[99],"Faster-RCNN":[101],"Feature":[103],"pyramid":[104],"network(FFPN)":[105],"[3].":[106],"gives":[108],"69/71.9%":[109],"same":[114],"reasonably":[118],"acceptable":[119],"performance.":[120],"Also,":[121],"both":[122],"evaluated":[127],"be":[129],"towards":[131],"noise.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}