{"id":"https://openalex.org/W2804822190","doi":"https://doi.org/10.1109/jstars.2018.2825099","title":"Detection of Vehicles in Multisensor Data via Multibranch Convolutional Neural Networks","display_name":"Detection of Vehicles in Multisensor Data via Multibranch Convolutional Neural Networks","publication_year":2018,"publication_date":"2018-05-24","ids":{"openalex":"https://openalex.org/W2804822190","doi":"https://doi.org/10.1109/jstars.2018.2825099","mag":"2804822190"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2018.2825099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2825099","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5091134997","display_name":"Hendrik Schilling","orcid":"https://orcid.org/0000-0001-9046-8931"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hendrik Schilling","raw_affiliation_strings":["Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9046-8931","affiliations":[{"raw_affiliation_string":"Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047379126","display_name":"Dimitri Bulatov","orcid":"https://orcid.org/0000-0002-0560-2591"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dimitri Bulatov","raw_affiliation_strings":["Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany"],"raw_orcid":"https://orcid.org/0000-0002-0560-2591","affiliations":[{"raw_affiliation_string":"Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026867229","display_name":"Robin Niessner","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Robin Niessner","raw_affiliation_strings":["Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075370224","display_name":"Wolfgang Middelmann","orcid":"https://orcid.org/0000-0002-3507-7396"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Middelmann","raw_affiliation_strings":["Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany"],"raw_orcid":"https://orcid.org/0000-0002-3507-7396","affiliations":[{"raw_affiliation_string":"Department of Scene Analysis, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Karlsruhe, Germany","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007703467","display_name":"Uwe Soergel","orcid":"https://orcid.org/0000-0002-4233-6405"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Uwe Soergel","raw_affiliation_strings":["Institute for Photogrammetry, University of Stuttgart, Stuttgart, Germany"],"raw_orcid":"https://orcid.org/0000-0002-4233-6405","affiliations":[{"raw_affiliation_string":"Institute for Photogrammetry, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":2.393,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.9194015,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":"11","first_page":"4299","last_page":"4316"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9957000017166138,"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/computer-science","display_name":"Computer science","score":0.8199527263641357},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7803144454956055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7074010968208313},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5770359635353088},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.5635024905204773},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.562789261341095},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5321965217590332},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5101211667060852},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.47309592366218567},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44925931096076965},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4353331923484802},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42714211344718933},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4191417098045349},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19453245401382446}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8199527263641357},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7803144454956055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7074010968208313},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5770359635353088},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.5635024905204773},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.562789261341095},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5321965217590332},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5101211667060852},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.47309592366218567},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44925931096076965},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4353331923484802},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42714211344718933},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4191417098045349},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19453245401382446}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jstars.2018.2825099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2018.2825099","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:fraunhofer.de:N-497303","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-497303.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IOSB","raw_type":"Journal Article"},{"id":"pmh:oai:publica.fraunhofer.de:publica/253226","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/253226","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"journal article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W11597023","https://openalex.org/W342017809","https://openalex.org/W639708223","https://openalex.org/W1594676769","https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W1904073808","https://openalex.org/W1905882502","https://openalex.org/W1955055330","https://openalex.org/W1972619302","https://openalex.org/W1973028189","https://openalex.org/W1979770060","https://openalex.org/W2002266720","https://openalex.org/W2016053056","https://openalex.org/W2022686119","https://openalex.org/W2049963111","https://openalex.org/W2061660999","https://openalex.org/W2063525734","https://openalex.org/W2066916495","https://openalex.org/W2088049833","https://openalex.org/W2088931003","https://openalex.org/W2095537868","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2124404372","https://openalex.org/W2133033754","https://openalex.org/W2140793580","https://openalex.org/W2141329296","https://openalex.org/W2145158371","https://openalex.org/W2163605009","https://openalex.org/W2163815613","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2253590344","https://openalex.org/W2292481059","https://openalex.org/W2324761925","https://openalex.org/W2384495648","https://openalex.org/W2399182745","https://openalex.org/W2410591237","https://openalex.org/W2412782625","https://openalex.org/W2440712233","https://openalex.org/W2488187315","https://openalex.org/W2512351403","https://openalex.org/W2517660364","https://openalex.org/W2525777026","https://openalex.org/W2527276685","https://openalex.org/W2548791488","https://openalex.org/W2551397753","https://openalex.org/W2567850185","https://openalex.org/W2574739416","https://openalex.org/W2587248218","https://openalex.org/W2592141703","https://openalex.org/W2592502477","https://openalex.org/W2602024454","https://openalex.org/W2604227478","https://openalex.org/W2605995529","https://openalex.org/W2610528085","https://openalex.org/W2613718673","https://openalex.org/W2613825824","https://openalex.org/W2618530766","https://openalex.org/W2620607813","https://openalex.org/W2750339080","https://openalex.org/W2778899074","https://openalex.org/W2962835968","https://openalex.org/W2963150697","https://openalex.org/W2963563573","https://openalex.org/W2963659230","https://openalex.org/W2963881378","https://openalex.org/W3105409087","https://openalex.org/W4244102296","https://openalex.org/W4251718368","https://openalex.org/W6600481126","https://openalex.org/W6637373629","https://openalex.org/W6712731584","https://openalex.org/W6715287400","https://openalex.org/W6722710385","https://openalex.org/W6736208988"],"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/W3209723314","https://openalex.org/W2952736415","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W2962677013"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,67],"networks,":[2],"or":[3,171,228],"CNNs,":[4],"raised":[5],"the":[6,52,62,86,100,142,199],"bar":[7],"for":[8,70,107,150],"most":[9],"computer":[10],"vision":[11],"problems":[12],"and":[13,77,148,189,204,219],"have":[14],"an":[15],"increasing":[16],"impact":[17],"in":[18,74,160],"remote":[19],"sensing.":[20],"However,":[21],"since":[22],"they":[23],"usually":[24],"contain":[25],"multiple":[26],"pooling":[27],"layers,":[28],"detection":[29,73,187],"of":[30,33,54,64,152,154,168,201],"exact":[31],"borders":[32],"small":[34],"objects":[35],"at":[36,103],"their":[37],"original":[38],"resolution":[39],"remains":[40],"yet":[41],"a":[42,95,104,119,135],"challenging":[43],"topic.":[44],"Additionally,":[45],"efforts":[46],"are":[47,112,163,235],"being":[48],"made":[49],"to":[50,128,208,245],"reduce":[51],"amount":[53],"training":[55,83,179,182],"data.":[56],"In":[57,193],"this":[58],"paper,":[59],"we":[60,90,197],"investigate":[61,198],"potential":[63],"fully":[65],"convolutional":[66],"networks":[68],"(FCNs)":[69],"individual":[71],"vehicle":[72],"combined":[75],"elevation":[76,220],"optical":[78,217],"data":[79,202],"using":[80],"relatively":[81],"few":[82,181],"samples.":[84],"By":[85],"proposed":[87],"multibranch":[88],"CNN,":[89],"combine":[91],"object":[92,101],"recognition":[93],"within":[94],"deep":[96],"learning":[97],"framework":[98],"with":[99,118,180,238],"segmentation":[102],"high":[105],"resolution,":[106],"which":[108,138,161],"two":[109],"CNN":[110],"branches":[111],"employed.":[113],"Data":[114],"fusion":[115,203],"is":[116,131,139],"accomplished":[117],"pseudo-Siamese":[120],"approach.":[121],"The":[122,232],"pixelwise":[123],"classification":[124],"likelihood,":[125],"also":[126],"referred":[127],"as":[129],"heatmap,":[130],"harmoniously":[132],"postprocessed":[133],"by":[134,166,172],"vectorization":[136],"module,":[137],"based":[140],"on":[141],"minimum":[143],"bounding":[144],"rectangle":[145],"(MBR)":[146],"extraction":[147],"allows":[149,177],"delineation":[151],"groups":[153],"vehicles.":[155],"Two":[156],"methods":[157],"were":[158,214],"developed":[159],"MBRs":[162],"supported":[164],"either":[165,223],"pairs":[167],"parallel":[169],"lines":[170],"region":[173],"growing.":[174],"Our":[175],"approach":[176,207],"efficient":[178],"samples,":[183],"while":[184],"delivering":[185],"high-quality":[186],"results":[188,234],"good":[190],"computational":[191],"performance.":[192],"our":[194,206],"detailed":[195],"evaluation,":[196],"benefits":[200],"compare":[205],"other":[209],"state-of-the-art":[210],"networks.":[211],"Different":[212],"datasets":[213],"used,":[215],"containing":[216],"images":[218],"data,":[221],"derived":[222],"from":[224,229],"airborne":[225],"laser":[226],"scanning":[227],"photogrammetric":[230],"reconstruction.":[231],"obtained":[233],"very":[236],"promising":[237],"F":[239],"<sub":[240],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[241],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[242],"scores":[243],"up":[244],"97%.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}