{"id":"https://openalex.org/W2079766420","doi":"https://doi.org/10.1109/scis-isis.2012.6505324","title":"Using gyroscopic sensors data with artificial neural networks for junction detection","display_name":"Using gyroscopic sensors data with artificial neural networks for junction detection","publication_year":2012,"publication_date":"2012-11-01","ids":{"openalex":"https://openalex.org/W2079766420","doi":"https://doi.org/10.1109/scis-isis.2012.6505324","mag":"2079766420"},"language":"en","primary_location":{"id":"doi:10.1109/scis-isis.2012.6505324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/scis-isis.2012.6505324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems","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/A5074490789","display_name":"Kenneth J. Mackin","orcid":null},"institutions":[{"id":"https://openalex.org/I14396692","display_name":"Tokyo University of Information Sciences","ror":"https://ror.org/044bdx604","country_code":"JP","type":"education","lineage":["https://openalex.org/I14396692"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kenneth J. Mackin","raw_affiliation_strings":["Tokyo University of Information Sciences, Japan","[Tokyo University of Information Sciences, Japan]"],"affiliations":[{"raw_affiliation_string":"Tokyo University of Information Sciences, Japan","institution_ids":["https://openalex.org/I14396692"]},{"raw_affiliation_string":"[Tokyo University of Information Sciences, Japan]","institution_ids":["https://openalex.org/I14396692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066865290","display_name":"Makoto Fujiyoshi","orcid":null},"institutions":[{"id":"https://openalex.org/I38674515","display_name":"Hitachi Zosen (Japan)","ror":"https://ror.org/05fvfp460","country_code":"JP","type":"company","lineage":["https://openalex.org/I38674515"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Makoto Fujiyoshi","raw_affiliation_strings":["Hitachi Zosen Corporation, Japan"],"affiliations":[{"raw_affiliation_string":"Hitachi Zosen Corporation, Japan","institution_ids":["https://openalex.org/I38674515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074490789"],"corresponding_institution_ids":["https://openalex.org/I14396692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13430693,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2027","last_page":"2028"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9379000067710876,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9379000067710876,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9323999881744385,"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"}},{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.9298999905586243,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/gyroscope","display_name":"Gyroscope","score":0.8960158824920654},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.7970097661018372},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6168531179428101},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6147093772888184},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.5664232969284058},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5420944690704346},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4383735656738281},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.43685874342918396},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.26882463693618774},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09864068031311035},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.09288126230239868}],"concepts":[{"id":"https://openalex.org/C158488048","wikidata":"https://www.wikidata.org/wiki/Q483400","display_name":"Gyroscope","level":2,"score":0.8960158824920654},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.7970097661018372},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6168531179428101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6147093772888184},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.5664232969284058},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5420944690704346},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4383735656738281},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.43685874342918396},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26882463693618774},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09864068031311035},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.09288126230239868}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/scis-isis.2012.6505324","is_oa":false,"landing_page_url":"https://doi.org/10.1109/scis-isis.2012.6505324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.47999998927116394,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1889129279","https://openalex.org/W4387451989","https://openalex.org/W2532412374","https://openalex.org/W2063137106","https://openalex.org/W2358715846","https://openalex.org/W2761234876","https://openalex.org/W2020920196","https://openalex.org/W4229455305","https://openalex.org/W2068060055","https://openalex.org/W2168042464"],"abstract_inverted_index":{"Gyroscopic":[0,29],"sensors":[1,23,30,76,83],"are":[2,49,79],"frequently":[3],"used":[4],"in":[5,9,69,97],"automotive":[6,106],"navigation":[7],"systems":[8],"order":[10,98],"to":[11,20,93,99,117],"improve":[12],"location":[13,27,37,85,103],"estimation":[14,38],"by":[15],"using":[16,112],"the":[17,80,101,105,119,122],"angle":[18],"information":[19],"supplement":[21],"other":[22],"such":[24],"as":[25],"GPS":[26,47,63],"data.":[28],"can":[31],"become":[32],"a":[33,60,70],"major":[34],"sensor":[35,95],"for":[36,39,44,84],"automobiles":[40],"or":[41,51,72],"autonomous":[42],"robots":[43],"situations":[45],"where":[46,62],"data":[48,64,96],"inaccurate":[50],"cannot":[52,65],"be":[53,66],"received.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58],"assume":[59],"situation":[61],"received,":[67],"e.g.":[68],"building":[71],"tunnel,":[73],"and":[74,77],"gyroscopic":[75,94],"speedometer":[78],"only":[81],"available":[82],"estimation.":[86],"We":[87,108],"propose":[88],"applying":[89],"artificial":[90],"neural":[91],"networks":[92],"estimate":[100],"current":[102],"of":[104,121],"device.":[107],"conducted":[109],"an":[110,113],"experiment":[111],"electric":[114],"model":[115],"railroad":[116],"verify":[118],"accuracy":[120],"proposed":[123],"method.":[124]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}