{"id":"https://openalex.org/W2899061465","doi":"https://doi.org/10.1145/3267305.3267531","title":"Benchmarking the SHL Recognition Challenge with Classical and Deep-Learning Pipelines","display_name":"Benchmarking the SHL Recognition Challenge with Classical and Deep-Learning Pipelines","publication_year":2018,"publication_date":"2018-10-08","ids":{"openalex":"https://openalex.org/W2899061465","doi":"https://doi.org/10.1145/3267305.3267531","mag":"2899061465"},"language":"en","primary_location":{"id":"doi:10.1145/3267305.3267531","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3267305.3267531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Benchmarking_the_SHL_Recognition_Challenge_with_classical_and_deep-learning_pipelines/23461394","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100403109","display_name":"Lin Wang","orcid":"https://orcid.org/0000-0001-8095-9518"},"institutions":[{"id":"https://openalex.org/I162608824","display_name":"University of Sussex","ror":"https://ror.org/00ayhx656","country_code":"GB","type":"education","lineage":["https://openalex.org/I162608824"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lin Wang","raw_affiliation_strings":["Wearable Technologies Lab, Sensor Technology Research Centre, University of Sussex, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wearable Technologies Lab, Sensor Technology Research Centre, University of Sussex, UK","institution_ids":["https://openalex.org/I162608824"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004955908","display_name":"Hristijan Gjoreski","orcid":"https://orcid.org/0000-0002-0770-4268"},"institutions":[{"id":"https://openalex.org/I4210157357","display_name":"University of Ss. Cyril and Methodius in Trnava","ror":"https://ror.org/04xdyq509","country_code":"SK","type":"education","lineage":["https://openalex.org/I4210157357"]}],"countries":["SK"],"is_corresponding":false,"raw_author_name":"Hristijan Gjoreski","raw_affiliation_strings":["Ss. Cyril and Methodius University, MK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ss. Cyril and Methodius University, MK","institution_ids":["https://openalex.org/I4210157357"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077861505","display_name":"Mathias Ciliberto","orcid":"https://orcid.org/0000-0001-9550-7637"},"institutions":[{"id":"https://openalex.org/I162608824","display_name":"University of Sussex","ror":"https://ror.org/00ayhx656","country_code":"GB","type":"education","lineage":["https://openalex.org/I162608824"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mathias Ciliberto","raw_affiliation_strings":["Wearable Technologies Lab, Sensor Technology Research Centre, University of Sussex, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wearable Technologies Lab, Sensor Technology Research Centre, University of Sussex, UK","institution_ids":["https://openalex.org/I162608824"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079783809","display_name":"Sami Mekki","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123571","display_name":"Huawei Technologies (France)","ror":"https://ror.org/02rbzf697","country_code":"FR","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210123571"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sami Mekki","raw_affiliation_strings":["Mathematical and Algorithmic Sciences, Lab, Huawei Technology, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematical and Algorithmic Sciences, Lab, Huawei Technology, France","institution_ids":["https://openalex.org/I4210123571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105877821","display_name":"Stefan Valentin","orcid":"https://orcid.org/0000-0003-4181-402X"},"institutions":[{"id":"https://openalex.org/I4210123571","display_name":"Huawei Technologies (France)","ror":"https://ror.org/02rbzf697","country_code":"FR","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210123571"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Stefan Valentin","raw_affiliation_strings":["Mathematical and Algorithmic Sciences, Lab, Huawei Technology, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mathematical and Algorithmic Sciences, Lab, Huawei Technology, France","institution_ids":["https://openalex.org/I4210123571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051210293","display_name":"Daniel Roggen","orcid":"https://orcid.org/0000-0001-8033-6417"},"institutions":[{"id":"https://openalex.org/I162608824","display_name":"University of Sussex","ror":"https://ror.org/00ayhx656","country_code":"GB","type":"education","lineage":["https://openalex.org/I162608824"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Daniel Roggen","raw_affiliation_strings":["Wearable Technologies Lab, Sensor Technology Research Centre, University of Sussex, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wearable Technologies Lab, Sensor Technology Research Centre, University of Sussex, UK","institution_ids":["https://openalex.org/I162608824"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1626","last_page":"1635"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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":0.9957000017166138,"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/computer-science","display_name":"Computer science","score":0.7452144026756287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7304254770278931},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6985048055648804},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6548218727111816},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6318519115447998},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.621446430683136},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.5956441164016724},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5556725859642029},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.47755226492881775},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.47710734605789185},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.41880857944488525},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4155365824699402},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.356797456741333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7452144026756287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7304254770278931},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6985048055648804},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6548218727111816},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6318519115447998},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.621446430683136},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5956441164016724},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5556725859642029},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.47755226492881775},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.47710734605789185},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.41880857944488525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4155365824699402},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.356797456741333},{"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/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3267305.3267531","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3267305.3267531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers","raw_type":"proceedings-article"},{"id":"pmh:oai:figshare.com:article/23461394","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Benchmarking_the_SHL_Recognition_Challenge_with_classical_and_deep-learning_pipelines/23461394","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference contribution"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/49728","is_oa":false,"landing_page_url":"http://qmro.qmul.ac.uk/xmlui/handle/123456789/49728","pdf_url":null,"source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"pmh:oai:sro.sussex.ac.uk:78510","is_oa":false,"landing_page_url":"http://sro.sussex.ac.uk/78510/1/ubicomp18g-sub1044-cam-i7.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400129","display_name":"Sussex Research Online (University of Sussex)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I162608824","host_organization_name":"University of Sussex","host_organization_lineage":["https://openalex.org/I162608824"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/23461394","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Benchmarking_the_SHL_Recognition_Challenge_with_classical_and_deep-learning_pipelines/23461394","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference contribution"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W944070795","https://openalex.org/W2095705004","https://openalex.org/W2098104834","https://openalex.org/W2101535084","https://openalex.org/W2108467170","https://openalex.org/W2108609368","https://openalex.org/W2113150374","https://openalex.org/W2153635508","https://openalex.org/W2270470215","https://openalex.org/W2743898215","https://openalex.org/W2763030746","https://openalex.org/W2883766876","https://openalex.org/W2899151654","https://openalex.org/W2907123474"],"related_works":["https://openalex.org/W4367336074","https://openalex.org/W4379620016","https://openalex.org/W3154045278","https://openalex.org/W3210764983","https://openalex.org/W4367335949","https://openalex.org/W3089416646","https://openalex.org/W4285162676","https://openalex.org/W4382052559","https://openalex.org/W3036529732","https://openalex.org/W2780266336"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we,":[3],"as":[4],"part":[5],"of":[6,37,86],"the":[7,28,72,89,98,103,113,128,133],"Sussex-Huawei":[8],"Locomotion-Transportation":[9],"(SHL)":[10],"Recognition":[11],"Challenge":[12],"organizing":[13],"team,":[14],"present":[15],"reference":[16],"recognition":[17,114],"performance":[18,130],"obtained":[19],"by":[20],"applying":[21],"various":[22],"classical":[23,56],"and":[24,53,67,77,101],"deep-learning":[25,73],"classifiers":[26,57,74],"to":[27,33,88,111],"testing":[29],"dataset.":[30],"We":[31,82,106],"aim":[32],"recognize":[34],"eight":[35],"modes":[36],"transportation":[38],"(Still,":[39],"Walk,":[40],"Run,":[41],"Bike,":[42],"Bus,":[43],"Car,":[44],"Train,":[45],"Subway)":[46],"from":[47],"smartphone":[48],"inertial":[49],"sensors:":[50],"accelerometer,":[51],"gyroscope":[52],"magnetometer.":[54],"The":[55],"include":[58,75],"naive":[59],"Bayesian,":[60],"decision":[61],"tree,":[62],"random":[63],"forest,":[64],"K-nearest":[65],"neighbour":[66],"support":[68],"vector":[69],"machine,":[70],"while":[71],"fully-connected":[76],"convolutional":[78,119],"deep":[79],"neural":[80,120],"networks.":[81],"feed":[83],"different":[84],"types":[85],"input":[87],"classifier,":[90],"including":[91],"hand-crafted":[92],"features,":[93],"raw":[94,125],"sensor":[95],"data":[96,126],"in":[97,102],"time":[99],"domain,":[100],"frequency":[104],"domain.":[105],"employ":[107],"a":[108],"post-processing":[109],"scheme":[110],"improve":[112],"performance.":[115],"Results":[116],"show":[117],"that":[118],"network":[121],"operating":[122],"on":[123],"frequency-domain":[124],"achieves":[127],"best":[129],"among":[131],"all":[132],"classifiers.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
