{"id":"https://openalex.org/W2790825277","doi":"https://doi.org/10.1109/tiv.2018.2873900","title":"Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble","display_name":"Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble","publication_year":2018,"publication_date":"2018-10-04","ids":{"openalex":"https://openalex.org/W2790825277","doi":"https://doi.org/10.1109/tiv.2018.2873900","mag":"2790825277"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2018.2873900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2018.2873900","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Intelligent Vehicles","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1803.03487","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Maarten Bieshaar","orcid":"https://orcid.org/0000-0002-6471-6062"},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maarten Bieshaar","raw_affiliation_strings":["Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany"],"raw_orcid":"https://orcid.org/0000-0002-6471-6062","affiliations":[{"raw_affiliation_string":"Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Stefan Zernetsch","orcid":"https://orcid.org/0000-0003-2016-5059"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Zernetsch","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0003-2016-5059","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andreas Hubert","orcid":null},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Hubert","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bernhard Sick","orcid":null},"institutions":[{"id":"https://openalex.org/I106157433","display_name":"University of Kassel","ror":"https://ror.org/04zc7p361","country_code":"DE","type":"education","lineage":["https://openalex.org/I106157433"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernhard Sick","raw_affiliation_strings":["Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Embedded Systems Lab, University of Kassel, Kassel, Germany","institution_ids":["https://openalex.org/I106157433"]}]},{"author_position":"last","author":{"id":null,"display_name":"Konrad Doll","orcid":"https://orcid.org/0000-0002-3746-2319"},"institutions":[{"id":"https://openalex.org/I4210158205","display_name":"Aschaffenburg University of Applied Sciences","ror":"https://ror.org/04sms9203","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210158205"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Konrad Doll","raw_affiliation_strings":["Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-3746-2319","affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Applied Sciences Aschaffenburg, Aschaffenburg, Germany","institution_ids":["https://openalex.org/I4210158205"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.456,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.82967252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"3","issue":"4","first_page":"534","last_page":"544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.5557000041007996,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.5557000041007996,"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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.13099999725818634,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.042899999767541885,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.7069000005722046},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6988999843597412},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6873000264167786},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.546999990940094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4634000062942505},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.44690001010894775},{"id":"https://openalex.org/keywords/cascading-classifiers","display_name":"Cascading classifiers","score":0.3785000145435333},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3662000000476837}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7314000129699707},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.7069000005722046},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6988999843597412},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6988000273704529},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6873000264167786},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.546999990940094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4634000062942505},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.44690001010894775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40950000286102295},{"id":"https://openalex.org/C40651066","wikidata":"https://www.wikidata.org/wiki/Q5048220","display_name":"Cascading classifiers","level":4,"score":0.3785000145435333},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3662000000476837},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.32580000162124634},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.3158000111579895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28839999437332153},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2669999897480011},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tiv.2018.2873900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2018.2873900","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Intelligent Vehicles","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1803.03487","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1803.03487","pdf_url":"https://arxiv.org/pdf/1803.03487","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1803.03487","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1803.03487","pdf_url":"https://arxiv.org/pdf/1803.03487","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8599740047","display_name":null,"funder_award_id":"SPP 1835","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1937999893","https://openalex.org/W1943054406","https://openalex.org/W1954601274","https://openalex.org/W1967592907","https://openalex.org/W1970490026","https://openalex.org/W1983364832","https://openalex.org/W2004641798","https://openalex.org/W2007122786","https://openalex.org/W2023302299","https://openalex.org/W2031638733","https://openalex.org/W2038420319","https://openalex.org/W2096937366","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2164685708","https://openalex.org/W2168089503","https://openalex.org/W2194775991","https://openalex.org/W2295598076","https://openalex.org/W2427105973","https://openalex.org/W2465597433","https://openalex.org/W2529122122","https://openalex.org/W2600003614","https://openalex.org/W2739667207","https://openalex.org/W2740801047","https://openalex.org/W2786725038","https://openalex.org/W2792977668","https://openalex.org/W2793720684","https://openalex.org/W2951183276","https://openalex.org/W4232478844","https://openalex.org/W6628785978","https://openalex.org/W6684191040","https://openalex.org/W6731907337","https://openalex.org/W6732520560","https://openalex.org/W6743005189","https://openalex.org/W6754384740"],"related_works":[],"abstract_inverted_index":{"In":[0,31],"the":[1,98],"future,":[2],"vehicles":[3],"and":[4,11,53,120],"other":[5],"traffic":[6],"participants":[7],"will":[8],"be":[9],"interconnected":[10],"equipped":[12],"with":[13,138],"various":[14],"types":[15],"of":[16,43,143],"sensors,":[17],"allowing":[18],"for":[19,39],"cooperation":[20],"on":[21,62,73,132],"different":[22],"levels,":[23],"such":[24],"as":[25],"situation":[26],"prediction":[27],"or":[28],"intention":[29],"detection.":[30],"this":[32],"paper,":[33],"we":[34],"present":[35],"a":[36,46,58,63,85,106,118],"cooperative":[37,123,130],"approach":[38,50,109,131],"starting":[40,71,89,124,145],"movement":[41,90,125],"detection":[42,91],"cyclists":[44],"using":[45,110],"boosted":[47],"stacking":[48,107],"ensemble":[49,108],"realizing":[51],"feature-":[52],"decision-level":[54],"cooperation.":[55],"We":[56,127],"introduce":[57],"novel":[59],"method":[60],"based":[61,88],"three-dimensional":[64],"convolutional":[65],"neural":[66],"network":[67],"(CNN)":[68],"to":[69],"detect":[70],"motions":[72],"image":[74],"sequences":[75],"by":[76,84,97],"learning":[77],"spatio-temporal":[78],"features.":[79],"The":[80],"CNN":[81],"is":[82],"complemented":[83],"smart":[86,94],"device":[87],"originating":[92,135],"from":[93,136],"devices":[95],"carried":[96],"cyclist.":[99],"Both":[100],"model":[101],"outputs":[102],"are":[103],"combined":[104],"in":[105,117],"an":[111],"extreme":[112],"gradient":[113],"boosting":[114],"classifier":[115],"resulting":[116],"fast":[119],"yet":[121],"robust":[122],"detector.":[126],"evaluate":[128],"our":[129],"real-world":[133],"data":[134],"experiments":[137],"49":[139],"test":[140],"subjects":[141],"consisting":[142],"84":[144],"motions.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2018-03-29T00:00:00"}
