{"id":"https://openalex.org/W2774742953","doi":"https://doi.org/10.18420/in2017_220","title":"Automated Annotation of Sensor data for Activity Recognition using Deep Learning","display_name":"Automated Annotation of Sensor data for Activity Recognition using Deep Learning","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2774742953","doi":"https://doi.org/10.18420/in2017_220","mag":"2774742953"},"language":"en","primary_location":{"id":"doi:10.18420/in2017_220","is_oa":true,"landing_page_url":"https://doi.org/10.18420/in2017_220","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.18420/in2017_220","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023826236","display_name":"Maik Benndorf","orcid":"https://orcid.org/0000-0002-3541-8787"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Benndorf, Maik","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071995239","display_name":"Frederic Ringsleben","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ringsleben, Frederic","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004205760","display_name":"Thomas Haenselmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haenselmann, Thomas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5053985804","display_name":"Bharat Yadav","orcid":"https://orcid.org/0000-0003-3121-6544"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yadav, Bharat","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023826236"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.49238539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2211","last_page":"2219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991999864578247,"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/annotation","display_name":"Annotation","score":0.5946854948997498},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5675422549247742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5527488589286804},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46510347723960876},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.4267827868461609},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34690573811531067},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3228655457496643}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5946854948997498},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5675422549247742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5527488589286804},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46510347723960876},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.4267827868461609},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34690573811531067},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3228655457496643}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18420/in2017_220","is_oa":true,"landing_page_url":"https://doi.org/10.18420/in2017_220","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:2774742953","is_oa":false,"landing_page_url":"https://dblp.uni-trier.de/db/conf/gi/gi2017.html#BenndorfRHY17","pdf_url":null,"source":{"id":"https://openalex.org/S4306511462","display_name":"GI-Jahrestagung","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"GI-Jahrestagung","raw_type":null}],"best_oa_location":{"id":"doi:10.18420/in2017_220","is_oa":true,"landing_page_url":"https://doi.org/10.18420/in2017_220","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W602397586","https://openalex.org/W1481578181","https://openalex.org/W2034899024","https://openalex.org/W2095975117","https://openalex.org/W2103388129","https://openalex.org/W2105990640","https://openalex.org/W2963274633","https://openalex.org/W2964304707","https://openalex.org/W3118608800"],"related_works":["https://openalex.org/W3004479835","https://openalex.org/W2973034414","https://openalex.org/W3164931747","https://openalex.org/W3190465639","https://openalex.org/W2805667690","https://openalex.org/W1979036471","https://openalex.org/W24270","https://openalex.org/W2954942310","https://openalex.org/W3087224943","https://openalex.org/W3028463090","https://openalex.org/W2906091377","https://openalex.org/W170288450","https://openalex.org/W2597131260","https://openalex.org/W2523983814","https://openalex.org/W2601877","https://openalex.org/W2622234887","https://openalex.org/W2766982279","https://openalex.org/W178048723","https://openalex.org/W2125617179","https://openalex.org/W2156129647"],"abstract_inverted_index":{"Within":[0],"this":[1,59,64],"work-in-progress,":[2],"we":[3,61,102],"aim":[4],"to":[5,92],"automate":[6],"the":[7,24,34,45,49,53,56,71,94,99,104],"annotation":[8],"of":[9,20,36,48,55,106],"Sensor":[10,72],"data":[11,15,73],"for":[12,16,83],"generating":[13],"training":[14],"Activity":[17],"Recognition":[18],"(AR)":[19],"multiple":[21],"persons.":[22],"Usually,":[23],"activities":[25,101],"are":[26],"executed":[27],"and":[28,52,69,88],"recorded":[29],"from":[30],"test":[31,50],"persons":[32,51],"under":[33],"supervision":[35],"an":[37],"instructor,":[38],"which":[39],"may":[40],"influence":[41,65],"in":[42],"many":[43],"cases":[44],"natural":[46],"behaviour":[47],"authenticity":[54],"data.":[57],"In":[58],"work,":[60],"suggest":[62],"how":[63,70],"can":[66,74],"be":[67,75],"reduced":[68],"annotated":[76],"automatically":[77,97],"by":[78],"using":[79],"video":[80],"capturing,":[81],"openpose":[82],"extracting":[84],"human":[85],"key":[86],"points":[87],"a":[89],"neuronal":[90],"network":[91],"classify":[93],"activities.":[95],"By":[96],"annotating":[98],"selected":[100],"show":[103],"feasibility":[105],"our":[107],"approach.":[108]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}