{"id":"https://openalex.org/W2791003324","doi":"https://doi.org/10.1109/itsc.2017.8317880","title":"DepthCN: Vehicle detection using 3D-LIDAR and ConvNet","display_name":"DepthCN: Vehicle detection using 3D-LIDAR and ConvNet","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2791003324","doi":"https://doi.org/10.1109/itsc.2017.8317880","mag":"2791003324"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2017.8317880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317880","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)","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/A5013510977","display_name":"Alireza Asvadi","orcid":"https://orcid.org/0000-0002-9645-5346"},"institutions":[{"id":"https://openalex.org/I76903346","display_name":"University of Coimbra","ror":"https://ror.org/04z8k9a98","country_code":"PT","type":"education","lineage":["https://openalex.org/I76903346"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"Alireza Asvadi","raw_affiliation_strings":["Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal","institution_ids":["https://openalex.org/I76903346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010345616","display_name":"Lu\u00eds Garrote","orcid":"https://orcid.org/0000-0003-3833-3794"},"institutions":[{"id":"https://openalex.org/I76903346","display_name":"University of Coimbra","ror":"https://ror.org/04z8k9a98","country_code":"PT","type":"education","lineage":["https://openalex.org/I76903346"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Luis Garrote","raw_affiliation_strings":["Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal","institution_ids":["https://openalex.org/I76903346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039508418","display_name":"Cristiano Premebida","orcid":"https://orcid.org/0000-0002-2168-2077"},"institutions":[{"id":"https://openalex.org/I76903346","display_name":"University of Coimbra","ror":"https://ror.org/04z8k9a98","country_code":"PT","type":"education","lineage":["https://openalex.org/I76903346"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Cristiano Premebida","raw_affiliation_strings":["Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal","institution_ids":["https://openalex.org/I76903346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059744952","display_name":"Paulo Peixoto","orcid":"https://orcid.org/0000-0002-3680-564X"},"institutions":[{"id":"https://openalex.org/I76903346","display_name":"University of Coimbra","ror":"https://ror.org/04z8k9a98","country_code":"PT","type":"education","lineage":["https://openalex.org/I76903346"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Paulo Peixoto","raw_affiliation_strings":["Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal","institution_ids":["https://openalex.org/I76903346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011728288","display_name":"Urbano Nunes","orcid":"https://orcid.org/0000-0002-7750-5221"},"institutions":[{"id":"https://openalex.org/I76903346","display_name":"University of Coimbra","ror":"https://ror.org/04z8k9a98","country_code":"PT","type":"education","lineage":["https://openalex.org/I76903346"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Urbano J. Nunes","raw_affiliation_strings":["Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering (DEEC), University of Coimbra, Coimbra, Portugal","institution_ids":["https://openalex.org/I76903346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5013510977"],"corresponding_institution_ids":["https://openalex.org/I76903346"],"apc_list":null,"apc_paid":null,"fwci":3.914,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.96329121,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9995999932289124,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8631337881088257},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7980204820632935},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7591049671173096},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6698631644248962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6504127979278564},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6496984362602234},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6490100622177124},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6419944167137146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5727521777153015},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.568640410900116},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5454323291778564},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48798245191574097},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.4759661555290222},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4358293116092682},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.21156105399131775},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09092390537261963},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0722968578338623}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8631337881088257},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7980204820632935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7591049671173096},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6698631644248962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6504127979278564},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6496984362602234},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6490100622177124},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6419944167137146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5727521777153015},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.568640410900116},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5454323291778564},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48798245191574097},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.4759661555290222},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4358293116092682},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.21156105399131775},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09092390537261963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0722968578338623},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2017.8317880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2017.8317880","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)","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":29,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1519128923","https://openalex.org/W1536680647","https://openalex.org/W1673310716","https://openalex.org/W1966456026","https://openalex.org/W1998372407","https://openalex.org/W2055207897","https://openalex.org/W2086197761","https://openalex.org/W2089815405","https://openalex.org/W2112796928","https://openalex.org/W2117248802","https://openalex.org/W2150066425","https://openalex.org/W2163605009","https://openalex.org/W2168356304","https://openalex.org/W2293349265","https://openalex.org/W2342242867","https://openalex.org/W2460157116","https://openalex.org/W2490270993","https://openalex.org/W2555618208","https://openalex.org/W2562105614","https://openalex.org/W2562674605","https://openalex.org/W2605189827","https://openalex.org/W2613718673","https://openalex.org/W2963083779","https://openalex.org/W4293682399","https://openalex.org/W6620707391","https://openalex.org/W6637131181","https://openalex.org/W6684191040","https://openalex.org/W6722946945"],"related_works":["https://openalex.org/W3192357901","https://openalex.org/W3036286480","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W4237171675","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W2962677013"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,33,47,92,99,109,121,126,146,161,166],"problem":[4],"of":[5,123,139,148],"vehicle":[6,28,103,153,163],"detection":[7,29,154,164],"using":[8,141],"Deep":[9],"Convolutional":[10],"Neural":[11],"Network":[12],"(ConvNet)":[13],"and":[14,24,37,144,158],"3D-LIDAR":[15,56],"data":[16,44,150],"with":[17],"application":[18],"in":[19],"advanced":[20],"driver":[21],"assistance":[22],"systems":[23],"autonomous":[25],"driving.":[26],"A":[27],"system":[30,48],"based":[31],"on":[32,58,152],"Hypothesis":[34],"Generation":[35],"(HG)":[36],"Verification":[38],"(HV)":[39],"paradigms":[40],"is":[41,49,64],"proposed.":[42],"The":[43,71],"inputted":[45],"to":[46,66,98,116,119,125,159],"a":[50,55,67,117],"point":[51,81],"cloud":[52,82],"obtained":[53],"from":[54],"mounted":[57],"board":[59],"an":[60,137],"instrumented":[61],"vehicle,":[62],"which":[63],"transformed":[65],"Dense-depth":[68],"Map":[69],"(DM).":[70],"proposed":[72,162],"solution":[73],"starts":[74],"by":[75,80],"removing":[76],"ground":[77],"points":[78],"followed":[79],"segmentation.":[83],"Then,":[84],"segmented":[85,100],"obstacles":[86],"(object":[87],"hypotheses)":[88],"are":[89,96,112],"projected":[90],"onto":[91],"DM.":[93],"Bounding":[94],"boxes":[95,111],"fitted":[97],"objects":[101],"as":[102,114],"hypotheses":[104,122],"(the":[105,129],"HG":[106],"step).":[107,131],"Finally,":[108],"bounding":[110],"used":[113],"inputs":[115],"ConvNet":[118,140],"classify/verify":[120],"belonging":[124],"category":[127],"`vehicle'":[128],"HV":[130],"In":[132],"this":[133],"paper,":[134],"we":[135],"present":[136],"evaluation":[138],"LIDAR-based":[142],"DMs":[143],"also":[145],"impact":[147],"domain-specific":[149],"augmentation":[151],"performance.":[155],"To":[156],"train":[157],"evaluate":[160],"system,":[165],"KITTI":[167],"Benchmark":[168],"Suite":[169],"was":[170],"used.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
