{"id":"https://openalex.org/W2770106921","doi":"https://doi.org/10.1145/3134230.3134231","title":"Deep Neural Network based Human Activity Recognition for the Order Picking Process","display_name":"Deep Neural Network based Human Activity Recognition for the Order Picking Process","publication_year":2017,"publication_date":"2017-09-21","ids":{"openalex":"https://openalex.org/W2770106921","doi":"https://doi.org/10.1145/3134230.3134231","mag":"2770106921"},"language":"en","primary_location":{"id":"doi:10.1145/3134230.3134231","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3134230.3134231","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction","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/A5048238299","display_name":"Ren\u00e9 Grzeszick","orcid":"https://orcid.org/0000-0001-7934-7469"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rene Grzeszick","raw_affiliation_strings":["Department of Computer Science, TU Dortmund University, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, TU Dortmund University, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055732232","display_name":"Jan Marius Lenk","orcid":null},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jan Marius Lenk","raw_affiliation_strings":["Department of Computer Science, TU Dortmund University, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, TU Dortmund University, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068918618","display_name":"Fernando Moya Rueda","orcid":"https://orcid.org/0000-0001-8115-5968"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fernando Moya Rueda","raw_affiliation_strings":["Department of Computer Science, TU Dortmund University, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, TU Dortmund University, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048407937","display_name":"Gernot A. Fink","orcid":"https://orcid.org/0000-0002-7446-7813"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gernot A. Fink","raw_affiliation_strings":["Department of Computer Science, TU Dortmund University, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, TU Dortmund University, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038422632","display_name":"Sascha Feldhorst","orcid":null},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]},{"id":"https://openalex.org/I4210098062","display_name":"Fraunhofer Institute for Material Flow and Logistics","ror":"https://ror.org/00z7dje19","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210098062","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sascha Feldhorst","raw_affiliation_strings":["Fraunhofer IML / Department of Mechanical Engineering, TU Dortmund University, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer IML / Department of Mechanical Engineering, TU Dortmund University, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995","https://openalex.org/I4210098062"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005976538","display_name":"Michael ten Hompel","orcid":"https://orcid.org/0000-0003-3349-4951"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]},{"id":"https://openalex.org/I4210098062","display_name":"Fraunhofer Institute for Material Flow and Logistics","ror":"https://ror.org/00z7dje19","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210098062","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael ten Hompel","raw_affiliation_strings":["Fraunhofer IML / Department of Mechanical Engineering, TU Dortmund University, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer IML / Department of Mechanical Engineering, TU Dortmund University, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995","https://openalex.org/I4210098062"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9104,"has_fulltext":false,"cited_by_count":90,"citation_normalized_percentile":{"value":0.93245734,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9749000072479248,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9749000072479248,"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9704999923706055,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/computer-science","display_name":"Computer science","score":0.8176669478416443},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7026657462120056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6524925231933594},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6370353698730469},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5741928815841675},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5597937107086182},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5330252647399902},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5197698473930359},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48762956261634827},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.48030680418014526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33188629150390625},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.32036060094833374},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.11766785383224487},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10727202892303467}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8176669478416443},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7026657462120056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6524925231933594},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6370353698730469},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5741928815841675},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5597937107086182},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5330252647399902},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5197698473930359},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48762956261634827},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.48030680418014526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33188629150390625},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.32036060094833374},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.11766785383224487},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10727202892303467},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3134230.3134231","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3134230.3134231","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-484198","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-484198.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 IML","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/399664","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/399664","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":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G3266177550","display_name":null,"funder_award_id":"Fi799/10-1","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":13,"referenced_works":["https://openalex.org/W1603086428","https://openalex.org/W1686810756","https://openalex.org/W2023302299","https://openalex.org/W2054780155","https://openalex.org/W2073401630","https://openalex.org/W2098481605","https://openalex.org/W2117539524","https://openalex.org/W2200813474","https://openalex.org/W2288074780","https://openalex.org/W2345270026","https://openalex.org/W2505886275","https://openalex.org/W2618530766","https://openalex.org/W2746223488"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4399254932"],"abstract_inverted_index":{"Although":[0],"the":[1,24,40,98,120,124,133,149,170],"fourth":[2],"industrial":[3,71,177],"revolution":[4],"is":[5,28,84,95,109,128],"already":[6],"in":[7,14,23,33,39,70,138,148,174],"pro-gress":[8],"and":[9,36,117,156],"advances":[10],"have":[11],"been":[12],"made":[13],"automating":[15],"factories,":[16],"completely":[17],"automated":[18],"facilities":[19],"are":[20,200],"still":[21,29],"far":[22],"future.":[25],"Human":[26],"work":[27,75],"an":[30],"important":[31],"factor":[32],"many":[34],"factories":[35],"warehouses,":[37],"especially":[38],"field":[41],"of":[42,67,101,144,172],"logistics.":[43],"Manual":[44],"processes":[45],"are,":[46],"therefore,":[47],"often":[48],"subject":[49],"to":[50,55,97,111],"optimization":[51,58],"efforts.":[52],"In":[53,73],"order":[54,134],"aid":[56],"these":[57],"efforts,":[59],"methods":[60],"like":[61],"human":[62],"activity":[63],"recognition":[64],"(HAR)":[65],"became":[66],"increasing":[68],"interest":[69],"settings.":[72],"this":[74],"a":[76,165,175],"novel":[77],"deep":[78],"neural":[79,88],"network":[80,89,108,150,168],"architecture":[81],"for":[82,163,169],"HAR":[83,173],"introduced.":[85],"A":[86],"convolutional":[87],"(CNN),":[90],"which":[91],"employs":[92],"temporal":[93],"convolutions,":[94],"applied":[96],"sequential":[99],"data":[100,131],"multiple":[102],"intertial":[103],"measurement":[104],"units":[105],"(IMUs).":[106],"The":[107,142],"designed":[110],"separately":[112],"handle":[113],"different":[114,140,145],"sensor":[115],"values":[116],"IMUs,":[118],"joining":[119],"information":[121],"step-by-step":[122],"within":[123],"architecture.":[125],"An":[126],"evaluation":[127],"performed":[129],"using":[130],"from":[132],"picking":[135],"process":[136],"recorded":[137],"two":[139],"warehouses.":[141],"influence":[143],"design":[146],"choices":[147],"architecture,":[151],"as":[152,154,194,196],"well":[153,195],"pre-":[155],"post-processing,":[157],"will":[158,179],"be":[159,180,185],"evaluated.":[160],"Crucial":[161],"steps":[162],"learning":[164],"good":[166],"classification":[167],"task":[171],"complex":[176],"setting":[178],"shown.":[181],"Ultimately,":[182],"it":[183],"can":[184],"shown":[186],"that":[187],"traditional":[188],"approaches":[189],"based":[190],"on":[191],"statistical":[192],"features":[193],"recent":[197],"CNN":[198],"architectures":[199],"outperformed.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":7}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}