{"id":"https://openalex.org/W3193981122","doi":"https://doi.org/10.1109/icip42928.2021.9506459","title":"Polynomial Trajectory Predictions for Improved Learning Performance","display_name":"Polynomial Trajectory Predictions for Improved Learning Performance","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3193981122","doi":"https://doi.org/10.1109/icip42928.2021.9506459","mag":"3193981122"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5016663410","display_name":"Ido Freeman","orcid":"https://orcid.org/0000-0003-4825-060X"},"institutions":[{"id":"https://openalex.org/I4210130520","display_name":"Aptiv (Germany)","ror":"https://ror.org/039sb8791","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210107152","https://openalex.org/I4210130520"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ido Freeman","raw_affiliation_strings":["Aptiv Services Deutschland GmbH,Wuppertal,Germany","Aptiv Services Deutschland GmbH, Wuppertal, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aptiv Services Deutschland GmbH,Wuppertal,Germany","institution_ids":["https://openalex.org/I4210130520"]},{"raw_affiliation_string":"Aptiv Services Deutschland GmbH, Wuppertal, Germany","institution_ids":["https://openalex.org/I4210130520"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047734667","display_name":"Kun Zhao","orcid":"https://orcid.org/0000-0003-3928-1981"},"institutions":[{"id":"https://openalex.org/I4210130520","display_name":"Aptiv (Germany)","ror":"https://ror.org/039sb8791","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210107152","https://openalex.org/I4210130520"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kun Zhao","raw_affiliation_strings":["Aptiv Services Deutschland GmbH,Wuppertal,Germany","Aptiv Services Deutschland GmbH, Wuppertal, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aptiv Services Deutschland GmbH,Wuppertal,Germany","institution_ids":["https://openalex.org/I4210130520"]},{"raw_affiliation_string":"Aptiv Services Deutschland GmbH, Wuppertal, Germany","institution_ids":["https://openalex.org/I4210130520"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080666933","display_name":"Anton Kummert","orcid":"https://orcid.org/0000-0002-0282-5087"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anton Kummert","raw_affiliation_strings":["University of Wuppertal,Faculty of Electrical, Information and Media Engineering,Germany","Faculty of Electrical, Information and Media Engineering, University of Wuppertal, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wuppertal,Faculty of Electrical, Information and Media Engineering,Germany","institution_ids":["https://openalex.org/I167360494"]},{"raw_affiliation_string":"Faculty of Electrical, Information and Media Engineering, University of Wuppertal, Germany","institution_ids":["https://openalex.org/I167360494"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"abs 1308 850","issue":null,"first_page":"3313","last_page":"3317"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"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":0.9994999766349792,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9879000186920166,"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/trajectory","display_name":"Trajectory","score":0.8583492040634155},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.6744934320449829},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.6594492793083191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6318443417549133},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5558112859725952},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5515815019607544},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4877351224422455},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.446257621049881},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4304152727127075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4167838990688324},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3408570885658264},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3236616849899292},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3205527067184448},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2224997878074646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.190311461687088},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.08891355991363525},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.07935202121734619}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8583492040634155},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.6744934320449829},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.6594492793083191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6318443417549133},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5558112859725952},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5515815019607544},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4877351224422455},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.446257621049881},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4304152727127075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4167838990688324},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3408570885658264},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3236616849899292},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3205527067184448},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2224997878074646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.190311461687088},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.08891355991363525},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.07935202121734619},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip42928.2021.9506459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","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":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W196162695","https://openalex.org/W1544016679","https://openalex.org/W1810943226","https://openalex.org/W1924770834","https://openalex.org/W2079291076","https://openalex.org/W2112222053","https://openalex.org/W2113517874","https://openalex.org/W2167052694","https://openalex.org/W2342840547","https://openalex.org/W2424778531","https://openalex.org/W2482392012","https://openalex.org/W2607296803","https://openalex.org/W2798182408","https://openalex.org/W2896642734","https://openalex.org/W2905173465","https://openalex.org/W2963001155","https://openalex.org/W2963150697","https://openalex.org/W2963906196","https://openalex.org/W2964396132","https://openalex.org/W2986406093","https://openalex.org/W3034217077","https://openalex.org/W3035096461","https://openalex.org/W4288287716","https://openalex.org/W4385245566","https://openalex.org/W6638273328","https://openalex.org/W6640212811","https://openalex.org/W6676797890","https://openalex.org/W6704559304","https://openalex.org/W6739901393","https://openalex.org/W6765361892","https://openalex.org/W6766110590","https://openalex.org/W6767342764"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W2989775562","https://openalex.org/W2002316083","https://openalex.org/W4224009465","https://openalex.org/W2062905336","https://openalex.org/W1629725936","https://openalex.org/W4312571183","https://openalex.org/W2150731338","https://openalex.org/W2108173372"],"abstract_inverted_index":{"The":[0],"rising":[1],"demand":[2],"for":[3,13,45],"Active":[4],"Safety":[5],"systems":[6],"in":[7,51],"automotive":[8],"applications":[9],"stresses":[10],"the":[11,22,33],"need":[12],"a":[14,56],"reliable":[15],"short-term":[16],"to":[17,31,41,65],"midterm":[18],"trajectory":[19],"prediction.":[20],"Anticipating":[21],"unfolding":[23],"path":[24],"of":[25,58],"road":[26],"users,":[27],"one":[28],"can":[29],"act":[30],"increase":[32,66],"overall":[34],"safety.":[35],"In":[36],"this":[37],"work,":[38],"we":[39],"propose":[40],"train":[42],"neural":[43],"networks":[44],"movement":[46],"understanding":[47],"by":[48],"predicting":[49],"trajectories":[50],"their":[52],"natural":[53],"form,":[54],"as":[55],"function":[57],"time.":[59],"Predicting":[60],"polynomial":[61],"coefficients":[62],"allows":[63],"us":[64],"accuracy":[67],"and":[68],"improve":[69],"generalisation.":[70]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}