{"id":"https://openalex.org/W4403212364","doi":"https://doi.org/10.1109/clei64178.2024.10700538","title":"AI-Based Point Cloud Upsampling for Autonomous Driving Systems","display_name":"AI-Based Point Cloud Upsampling for Autonomous Driving Systems","publication_year":2024,"publication_date":"2024-08-12","ids":{"openalex":"https://openalex.org/W4403212364","doi":"https://doi.org/10.1109/clei64178.2024.10700538"},"language":"en","primary_location":{"id":"doi:10.1109/clei64178.2024.10700538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei64178.2024.10700538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 L Latin American Computer Conference (CLEI)","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/A5109797097","display_name":"Nicol\u00e1s Salom\u00f3n","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nicol\u00e1s Salom\u00f3n","raw_affiliation_strings":["Fundación Fulgor,Córdoba,Argentina"],"affiliations":[{"raw_affiliation_string":"Fundación Fulgor,Córdoba,Argentina","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058156675","display_name":"Claudio Delrieux","orcid":"https://orcid.org/0000-0002-2727-8374"},"institutions":[{"id":"https://openalex.org/I56858762","display_name":"Universidad Nacional del Sur","ror":"https://ror.org/028crwz56","country_code":"AR","type":"education","lineage":["https://openalex.org/I56858762"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Claudio A. Delrieux","raw_affiliation_strings":["Universidad Nacional del Sur Bahía,Departamento de Ingeniería Eléctrica y Computadoras,Blanca,Argentina"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional del Sur Bahía,Departamento de Ingeniería Eléctrica y Computadoras,Blanca,Argentina","institution_ids":["https://openalex.org/I56858762"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107820909","display_name":"Leandro E. Borgnino","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leandro E. Borgnino","raw_affiliation_strings":["Universidad Nacional de Córdoba,Departamento de Electrónica,Córdoba,Argentina"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional de Córdoba,Departamento de Electrónica,Córdoba,Argentina","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017975249","display_name":"Dami\u00e1n A. Morero","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dami\u00e1n A. Morero","raw_affiliation_strings":["Universidad Nacional de Córdoba,Laboratorio de Comunicaciones Digitales,Córdoba,Argentina"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional de Córdoba,Laboratorio de Comunicaciones Digitales,Córdoba,Argentina","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109797097"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13074414,"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":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9485999941825867,"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/T12698","display_name":"3D Modeling in Geospatial Applications","score":0.9305999875068665,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/upsampling","display_name":"Upsampling","score":0.8384076356887817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7378038167953491},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.735612690448761},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.59025639295578},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38797834515571594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3754461407661438},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3447152376174927},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.08961799740791321},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06661367416381836}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8384076356887817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7378038167953491},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.735612690448761},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.59025639295578},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38797834515571594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3754461407661438},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3447152376174927},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.08961799740791321},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06661367416381836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/clei64178.2024.10700538","is_oa":false,"landing_page_url":"https://doi.org/10.1109/clei64178.2024.10700538","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 L Latin American Computer Conference (CLEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2849918157","https://openalex.org/W2914821954","https://openalex.org/W2963680153","https://openalex.org/W2968296999","https://openalex.org/W2997337685","https://openalex.org/W3091021773","https://openalex.org/W3164635536","https://openalex.org/W4285102191","https://openalex.org/W4311897594","https://openalex.org/W4313327218","https://openalex.org/W4389735977","https://openalex.org/W4394977914","https://openalex.org/W6631190155","https://openalex.org/W6745935785"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4385574037","https://openalex.org/W4386075645","https://openalex.org/W3176213335"],"abstract_inverted_index":{"Autonomous":[0],"driving,":[1],"decades":[2],"ago":[3],"relegated":[4],"to":[5,55,141,220],"the":[6,20,32,36,39,43,57,65,72,79,111,121,151,155,171,175,192,195,213,228],"realm":[7],"of":[8,34,47,71,81,113,125,154,197,232],"science":[9],"fiction,":[10],"emerged":[11],"as":[12,224],"a":[13,90,146],"tangible":[14],"reality":[15],"that":[16],"is":[17,69,104],"rapidly":[18],"transforming":[19],"automotive":[21],"industry,":[22],"redefining":[23],"our":[24,233],"relationship":[25],"with":[26,64,85,89,97,135,174],"vehicles,":[27],"and":[28,38,45,49,60,117,123,149,181,185,194,230],"placing":[29],"them":[30],"in":[31,139,166,183,235],"spotlight":[33],"both":[35],"industry":[37],"general":[40],"public.":[41],"Through":[42],"study":[44],"analysis":[46,112],"modern":[48],"efficient":[50],"interpolation":[51,87,127,160],"techniques,":[52,88,161],"we":[53],"aim":[54],"reduce":[56],"current":[58],"costs":[59],"processing":[61],"requirements":[62],"associated":[63],"LiDAR":[66,83,100,115],"sensor,":[67],"which":[68],"one":[70],"main":[73,108],"information":[74],"sources.":[75],"Our":[76],"approach":[77,234],"explores":[78],"fusion":[80],"lower-cost":[82],"sensors":[84],"advanced":[86],"particular":[91],"focus":[92],"on":[93,106,130,191],"achieving":[94],"performance":[95],"parity":[96],"pricier":[98],"64-channel":[99],"setups.":[101],"This":[102,226],"work":[103],"based":[105,129],"3":[107],"axes:":[109],"firstly,":[110],"available":[114],"data":[116,143],"its":[118],"representation;":[119],"secondly,":[120],"development":[122],"implementation":[124],"an":[126],"technique":[128],"1D":[131],"convolutional":[132],"layers":[133],"integrated":[134],"fully":[136],"connected":[137],"layers,":[138],"order":[140],"analyse":[142],"coming":[144],"from":[145],"sliding":[147],"window;":[148],"finally,":[150],"comparative":[152],"evaluation":[153],"results":[156],"between":[157,179],"different":[158],"state-of-the-art":[159],"using":[162],"object":[163,193],"detection":[164,184,198],"networks":[165],"point":[167,172],"clouds.":[168],"By":[169],"interpolating":[170],"clouds":[173],"proposed":[176],"technique,":[177],"improvements":[178],"1.92%":[180],"30.98%":[182],"classification":[186],"tasks":[187],"were":[188],"achieved,":[189],"depending":[190],"type":[196],"(3D":[199],"or":[200],"bird's":[201],"eye":[202],"view).":[203],"Furthermore,":[204],"computational":[205],"efficiency":[206],"was":[207],"not":[208],"left":[209],"aside":[210],"by":[211],"reducing":[212],"inference":[214],"times":[215],"necessary":[216],"for":[217],"interpolation,":[218],"compared":[219],"other":[221],"techniques":[222],"used":[223],"contrast.":[225],"highlights":[227],"viability":[229],"scalability":[231],"realizing":[236],"cost-effective":[237],"yet":[238],"high-perfermance":[239],"autonomous":[240],"driving":[241],"systems.":[242]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}