{"id":"https://openalex.org/W4409537019","doi":"https://doi.org/10.1109/icvisp64524.2024.10959343","title":"Distance Estimation by Fusion of Monocular Ranging and MMW Radar Information","display_name":"Distance Estimation by Fusion of Monocular Ranging and MMW Radar Information","publication_year":2024,"publication_date":"2024-12-27","ids":{"openalex":"https://openalex.org/W4409537019","doi":"https://doi.org/10.1109/icvisp64524.2024.10959343"},"language":"en","primary_location":{"id":"doi:10.1109/icvisp64524.2024.10959343","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp64524.2024.10959343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Vision, Image and Signal Processing (ICVISP)","raw_type":"proceedings-article"},"type":"conference-paper","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":null,"display_name":"QiRui Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"QiRui Cui","raw_affiliation_strings":["School of engineer, Huzhou University,Huzhou,Zhejiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of engineer, Huzhou University,Huzhou,Zhejiang,China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102939947","display_name":"Ye Chen","orcid":"https://orcid.org/0009-0004-5832-7361"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Chen","raw_affiliation_strings":["School of engineer, Huzhou University,Huzhou,Zhejiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of engineer, Huzhou University,Huzhou,Zhejiang,China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059684265","display_name":"ShunGeng Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ShunGeng Wang","raw_affiliation_strings":["School of engineer, Huzhou University,Huzhou,Zhejiang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of engineer, Huzhou University,Huzhou,Zhejiang,China","institution_ids":["https://openalex.org/I3018263800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3018263800"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9943000078201294,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9943000078201294,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9610000252723694,"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/ranging","display_name":"Ranging","score":0.8843899369239807},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5514451861381531},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5023763179779053},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.49362242221832275},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.46833181381225586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4354909658432007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42438894510269165},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.42069047689437866},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2407698929309845},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2189103066921234}],"concepts":[{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.8843899369239807},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5514451861381531},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5023763179779053},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.49362242221832275},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.46833181381225586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4354909658432007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42438894510269165},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42069047689437866},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2407698929309845},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2189103066921234},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icvisp64524.2024.10959343","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp64524.2024.10959343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 8th International Conference on Vision, Image and Signal Processing (ICVISP)","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":15,"referenced_works":["https://openalex.org/W2888375042","https://openalex.org/W3007598241","https://openalex.org/W3033934310","https://openalex.org/W3038835693","https://openalex.org/W3118578253","https://openalex.org/W3132342445","https://openalex.org/W3173112500","https://openalex.org/W4312667262","https://openalex.org/W4319596424","https://openalex.org/W4320713382","https://openalex.org/W4386450244","https://openalex.org/W4388240367","https://openalex.org/W4390783800","https://openalex.org/W4394676676","https://openalex.org/W4400727795"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W2594043982","https://openalex.org/W3036493597","https://openalex.org/W2351984678","https://openalex.org/W2140032575","https://openalex.org/W2011860471","https://openalex.org/W2012196540","https://openalex.org/W3011451421"],"abstract_inverted_index":{"A":[0],"single":[1],"sensor":[2,40,77,116,141],"often":[3],"fails":[4],"to":[5,80,111,126],"provide":[6],"comprehensive":[7],"and":[8,29,84,149],"reliable":[9],"information":[10],"in":[11,49],"complex":[12],"environments.":[13],"However,":[14],"multi-sensor":[15],"fusion":[16],"leverages":[17],"the":[18,32,113,136,151],"complementary":[19],"strengths":[20],"of":[21,34,115,153],"different":[22],"sensors,":[23],"fully":[24],"utilizing":[25],"their":[26],"measurement":[27,51,63,82,98,142,147],"capabilities":[28],"effectively":[30,139],"mitigating":[31],"limitations":[33],"individual":[35],"sensors.":[36,131],"In":[37],"practical":[38,154],"applications,":[39],"data":[41,128],"is":[42,71,109,124],"frequently":[43],"influenced":[44],"by":[45],"environmental":[46],"noise,":[47,143],"resulting":[48],"increased":[50],"errors.":[52],"To":[53],"overcome":[54],"this":[55,57],"challenge,":[56],"paper":[58],"presents":[59],"a":[60,92,105],"monocular":[61,96],"distance":[62,97,146],"model":[64,94,108],"based":[65,99],"on":[66,100],"object":[67,101],"detection":[68,102],"algorithms,":[69],"which":[70],"combined":[72],"with":[73,119],"millimeter-wave":[74],"radar":[75],"for":[76,95],"fusion,":[78],"aiming":[79],"enhance":[81],"accuracy":[83],"system":[85],"robustness.":[86],"The":[87],"proposed":[88,137],"method":[89],"first":[90],"constructs":[91],"geometric":[93],"algorithms.":[103],"Subsequently,":[104],"dynamic":[106],"error":[107],"introduced":[110],"address":[112],"issue":[114],"errors":[117],"varying":[118],"distance.":[120],"Finally,":[121],"Kalman":[122],"filtering":[123],"applied":[125],"fuse":[127],"from":[129],"multiple":[130],"Simulation":[132],"results":[133],"demonstrate":[134],"that":[135],"approach":[138],"reduces":[140],"significantly":[144],"improves":[145],"accuracy,":[148],"meets":[150],"requirements":[152],"applications.":[155]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}