{"id":"https://openalex.org/W4391678067","doi":"https://doi.org/10.1109/sii58957.2024.10417704","title":"Automatic Segmentation of Continuous Time-Series Data Based on Prediction Error Using Deep Predictive Learning","display_name":"Automatic Segmentation of Continuous Time-Series Data Based on Prediction Error Using Deep Predictive Learning","publication_year":2024,"publication_date":"2024-01-08","ids":{"openalex":"https://openalex.org/W4391678067","doi":"https://doi.org/10.1109/sii58957.2024.10417704"},"language":"en","primary_location":{"id":"doi:10.1109/sii58957.2024.10417704","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/sii58957.2024.10417704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/SICE International Symposium on System Integration (SII)","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/A5054052957","display_name":"Suzuka Harada","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]},{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Suzuka Harada","raw_affiliation_strings":["Waseda University,Faculty of Science and engineering,Department of Intermedia arts and Science,Tokyo,Japan,169-8050","National Institute of Advanced Industrial Science and Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Faculty of Science and engineering,Department of Intermedia arts and Science,Tokyo,Japan,169-8050","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029075114","display_name":"Ryoichi Nakajo","orcid":"https://orcid.org/0009-0006-3870-8508"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]},{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryoichi Nakajo","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology,Tokyo,Japan,100-8921","Department of Intermedia arts and Science, Faculty of Science and engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology,Tokyo,Japan,100-8921","institution_ids":["https://openalex.org/I73613424"]},{"raw_affiliation_string":"Department of Intermedia arts and Science, Faculty of Science and engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010195602","display_name":"Kei Kase","orcid":"https://orcid.org/0000-0003-4009-5254"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]},{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kei Kase","raw_affiliation_strings":["Waseda University,Faculty of Science and engineering,Department of Intermedia arts and Science,Tokyo,Japan,169-8050","National Institute of Advanced Industrial Science and Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Faculty of Science and engineering,Department of Intermedia arts and Science,Tokyo,Japan,169-8050","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055922202","display_name":"Tetsuya Ogata","orcid":"https://orcid.org/0000-0001-7015-0379"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]},{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Ogata","raw_affiliation_strings":["Waseda University,Faculty of Science and engineering,Department of Intermedia arts and Science,Tokyo,Japan,169-8050","National Institute of Advanced Industrial Science and Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Faculty of Science and engineering,Department of Intermedia arts and Science,Tokyo,Japan,169-8050","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01086408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"928","last_page":"933"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973999857902527,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973999857902527,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9688000082969666,"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/computer-science","display_name":"Computer science","score":0.6690323352813721},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.658296525478363},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.5984004139900208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5888750553131104},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5807932615280151},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5163063406944275},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45332494378089905},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4487456679344177},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3778318464756012},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3705078363418579},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06722885370254517}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6690323352813721},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.658296525478363},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.5984004139900208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5888750553131104},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5807932615280151},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5163063406944275},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45332494378089905},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4487456679344177},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3778318464756012},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3705078363418579},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06722885370254517},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sii58957.2024.10417704","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/sii58957.2024.10417704","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6725152017","display_name":null,"funder_award_id":"JPNP20006","funder_id":"https://openalex.org/F4320321034","funder_display_name":"New Energy and Industrial Technology Development Organization"}],"funders":[{"id":"https://openalex.org/F4320321034","display_name":"New Energy and Industrial Technology Development Organization","ror":"https://ror.org/0055k7a87"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1726806267","https://openalex.org/W1982486572","https://openalex.org/W2005958977","https://openalex.org/W2089029564","https://openalex.org/W2115279061","https://openalex.org/W2148463593","https://openalex.org/W2158190429","https://openalex.org/W2172230296","https://openalex.org/W2477205648","https://openalex.org/W2972891548","https://openalex.org/W2981952374","https://openalex.org/W3090715080","https://openalex.org/W3098201885","https://openalex.org/W4299828299","https://openalex.org/W4312868434","https://openalex.org/W6623576839","https://openalex.org/W6681753794","https://openalex.org/W6686207219","https://openalex.org/W6730042849","https://openalex.org/W6784155536"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W1919101720","https://openalex.org/W2731899572","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660","https://openalex.org/W155406958","https://openalex.org/W4387088901"],"abstract_inverted_index":{"In":[0,12,97],"deep":[1],"learning,":[2,15],"training":[3],"with":[4,93,196],"multiple":[5,137],"modalities":[6,24],"generally":[7],"improves":[8,41],"the":[9,42,86,159,168,174,197,201],"learning":[10,78,104,145,170,207],"performance.":[11],"robot":[13,119,124],"motion":[14,45],"human":[16,94],"knowledge":[17,95],"information":[18],"can":[19,126,148],"be":[20,91,127],"regarded":[21],"as":[22,72,117,129],"additional":[23],"and":[25,76,89,166],"aids":[26],"robots":[27],"to":[28,84,110,177,211],"perform":[29],"their":[30],"tasks.":[31],"Previous":[32],"studies":[33],"have":[34],"shown":[35],"that":[36,123,147,187,204],"annotation":[37],"of":[38,44,52,55,113,131,136,192],"action":[39,87],"segments":[40,88],"generalizability":[43],"learning.":[46,155],"However,":[47],"manual":[48,59],"segmentation":[49,53,60,67,112,175],"causes":[50],"inconsistencies":[51],"because":[54],"its":[56,179],"subjectivity,":[57],"Additionally":[58],"is":[61,80,162],"time-consuming":[62],"for":[63],"large-scale":[64],"datasets.":[65],"Automatic":[66],"by":[68],"generative":[69],"models,":[70,79],"such":[71],"hidden":[73,198],"Markov":[74,199],"models":[75],"predictive":[77,103,154,169,206],"an":[81],"alternative":[82],"approach":[83],"find":[85],"may":[90],"replaced":[92],"information.":[96,194],"this":[98],"study,":[99],"we":[100,142],"expand":[101],"a":[102,118,144,184,189],"model":[105,146,171,208],"using":[106],"recurrent":[107],"neural":[108],"networks":[109],"automatic":[111],"continuous":[114,160],"time-series":[115],"data":[116,150,161],"behavior.":[120],"We":[121,182],"assume":[122],"behavior":[125],"described":[128],"sequences":[130],"complex":[132],"time":[133,190],"series":[134,191],"composed":[135],"simple":[138],"patterns.":[139],"As":[140],"such,":[141],"utilize":[143],"segment":[149],"into":[151],"patterns":[152],"through":[153],"To":[156],"do":[157],"so,":[158],"first":[163],"segmented":[164],"equally,":[165],"next":[167],"autonomously":[172],"shifts":[173],"boundaries":[176],"minimize":[178],"prediction":[180],"error.":[181],"conducted":[183],"numerical":[185],"experiment":[186],"simulates":[188],"sensor":[193],"Comparing":[195],"model,":[200],"results":[202],"showed":[203],"our":[205],"were":[209],"able":[210],"estimate":[212],"more":[213],"suitable":[214],"segmenting":[215],"points.":[216]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
