{"id":"https://openalex.org/W4392248751","doi":"https://doi.org/10.1109/icce59016.2024.10444235","title":"Performance Enhancement using Data Augmentation of Depth Estimation for Autonomous Driving","display_name":"Performance Enhancement using Data Augmentation of Depth Estimation for Autonomous Driving","publication_year":2024,"publication_date":"2024-01-06","ids":{"openalex":"https://openalex.org/W4392248751","doi":"https://doi.org/10.1109/icce59016.2024.10444235"},"language":"en","primary_location":{"id":"doi:10.1109/icce59016.2024.10444235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","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/A5100925158","display_name":"Ji\u2010Sang Yoo","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jisang Yoo","raw_affiliation_strings":["Dong Seoul University,ADLab, MODULABS,Republic of Korea","ADLab, MODULABS, Dong Seoul University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Dong Seoul University,ADLab, MODULABS,Republic of Korea","institution_ids":[]},{"raw_affiliation_string":"ADLab, MODULABS, Dong Seoul University, Republic of Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101248498","display_name":"Woomin Jun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Woomin Jun","raw_affiliation_strings":["Dong Seoul University,ADLab, MODULABS,Republic of Korea","ADLab, MODULABS, Dong Seoul University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Dong Seoul University,ADLab, MODULABS,Republic of Korea","institution_ids":[]},{"raw_affiliation_string":"ADLab, MODULABS, Dong Seoul University, Republic of Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059843397","display_name":"Sung Lee","orcid":"https://orcid.org/0000-0001-9852-6999"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sungjin Lee","raw_affiliation_strings":["Dong Seoul University,ADLab, MODULABS,Republic of Korea","ADLab, MODULABS, Dong Seoul University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Dong Seoul University,ADLab, MODULABS,Republic of Korea","institution_ids":[]},{"raw_affiliation_string":"ADLab, MODULABS, Dong Seoul University, Republic of Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100925158"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01853467,"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":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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":0.9990000128746033,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/computer-science","display_name":"Computer science","score":0.6257767081260681},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.527506947517395},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3404492139816284},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32951056957244873},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1825750768184662}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6257767081260681},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.527506947517395},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3404492139816284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32951056957244873},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1825750768184662},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce59016.2024.10444235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce59016.2024.10444235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5099999904632568}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1915250530","https://openalex.org/W1976514650","https://openalex.org/W1983364832","https://openalex.org/W2118304946","https://openalex.org/W2124907686","https://openalex.org/W2125416623","https://openalex.org/W2150066425","https://openalex.org/W2151646056","https://openalex.org/W2194775991","https://openalex.org/W2259424905","https://openalex.org/W2343077198","https://openalex.org/W2520707372","https://openalex.org/W2534461033","https://openalex.org/W2593414960","https://openalex.org/W2609883120","https://openalex.org/W2792170448","https://openalex.org/W2798927139","https://openalex.org/W2883362496","https://openalex.org/W2891958727","https://openalex.org/W2912836860","https://openalex.org/W2928601293","https://openalex.org/W2951234442","https://openalex.org/W2962804601","https://openalex.org/W2962816904","https://openalex.org/W2963110069","https://openalex.org/W2963583471","https://openalex.org/W2963591054","https://openalex.org/W2963645879","https://openalex.org/W2964014680","https://openalex.org/W2967550825","https://openalex.org/W2981207549","https://openalex.org/W2985775862","https://openalex.org/W3002118011","https://openalex.org/W3006017979","https://openalex.org/W3034428934","https://openalex.org/W3034452391","https://openalex.org/W3107389224","https://openalex.org/W3119315021","https://openalex.org/W3128121047","https://openalex.org/W4243425824","https://openalex.org/W4285803579","https://openalex.org/W4295184807","https://openalex.org/W4386076222","https://openalex.org/W4386723894","https://openalex.org/W6637373629","https://openalex.org/W6685261749","https://openalex.org/W6753941181","https://openalex.org/W6759084196"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"For":[0],"autonomous":[1,63],"driving,":[2],"various":[3],"sensors":[4,20,41],"such":[5],"as":[6],"cameras,":[7,77],"LiDAR,":[8],"and":[9,32,50,84,136],"radar":[10,95],"are":[11],"required":[12],"to":[13,72,79,103,118],"accurately":[14],"perceive":[15],"the":[16,55,81,105,123,144,167],"surrounding":[17,124],"environment.":[18,125],"These":[19,52],"provide":[21],"information":[22,37,121],"for":[23,42],"tasks":[24,44],"like":[25],"object":[26],"recognition,":[27],"lane":[28],"detection,":[29],"path":[30],"planning,":[31],"distance":[33],"estimation.":[34],"However,":[35],"processing":[36],"from":[38,92],"these":[39],"multiple":[40],"perception":[43,74],"demands":[45],"significant":[46],"costs,":[47],"computational":[48,82],"resources,":[49],"latency.":[51],"challenges":[53],"hinder":[54],"practical":[56],"implementation":[57],"of":[58,107,146,169],"real-time":[59],"edge":[60],"computing":[61],"in":[62],"driving":[64],"systems.":[65],"Consequently,":[66],"research":[67],"is":[68],"actively":[69],"exploring":[70],"methods":[71],"perform":[73],"using":[75],"only":[76],"particularly":[78],"alleviate":[80],"burden":[83],"cost":[85],"associated":[86],"with":[87],"3D":[88,120],"point":[89],"cloud":[90],"data":[91,133,138,158],"LiDAR":[93],"or":[94],"sensors.":[96],"In":[97],"this":[98,170],"study,":[99],"we":[100,142],"investigate":[101],"techniques":[102,135],"optimize":[104],"performance":[106],"Monocular":[108],"Depth":[109],"Estimation":[110],"(MDE)":[111],"methods,":[112],"which":[113],"utilize":[114],"a":[115],"single":[116],"camera":[117],"extract":[119],"about":[122],"We":[126],"focus":[127],"on":[128],"enhancing":[129],"accuracy":[130],"through":[131],"classical":[132],"augmentation":[134,159],"synthetic":[137],"generation":[139],"methods.":[140],"Additionally,":[141],"explore":[143],"selection":[145],"an":[147],"optimal":[148],"loss":[149],"function.":[150],"Experimental":[151],"results":[152],"demonstrate":[153],"that":[154],"employing":[155],"our":[156],"proposed":[157],"approach":[160],"reduces":[161],"REL":[162],"by":[163],"approximately":[164],"3.9%,":[165],"showcasing":[166],"potential":[168],"method.":[171]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}