{"id":"https://openalex.org/W4388118938","doi":"https://doi.org/10.23919/eusipco58844.2023.10289719","title":"Semi-Supervised Convolutional Autoencoder With Attention Mechanism for Activity Recognition","display_name":"Semi-Supervised Convolutional Autoencoder With Attention Mechanism for Activity Recognition","publication_year":2023,"publication_date":"2023-09-04","ids":{"openalex":"https://openalex.org/W4388118938","doi":"https://doi.org/10.23919/eusipco58844.2023.10289719"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco58844.2023.10289719","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/eusipco58844.2023.10289719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","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/A5014996863","display_name":"Zahra Sadeghi-Adl","orcid":null},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zahra Sadeghi-Adl","raw_affiliation_strings":["Temple University,Department of Electrical and Computer Engineering,Philadelphia,PA,USA,19122"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Temple University,Department of Electrical and Computer Engineering,Philadelphia,PA,USA,19122","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083732517","display_name":"Fauzia Ahmad","orcid":"https://orcid.org/0000-0002-1446-5154"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fauzia Ahmad","raw_affiliation_strings":["Temple University,Department of Electrical and Computer Engineering,Philadelphia,PA,USA,19122"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Temple University,Department of Electrical and Computer Engineering,Philadelphia,PA,USA,19122","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1025,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41289652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"785","last_page":"789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12740","display_name":"Gait Recognition and Analysis","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/autoencoder","display_name":"Autoencoder","score":0.9592113494873047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7607459425926208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7037950158119202},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6946624517440796},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6890056729316711},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5191646814346313},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5006554126739502},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.4569542407989502},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.45065778493881226},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4242130517959595},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4150097668170929},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32819145917892456},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.21925082802772522}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9592113494873047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7607459425926208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7037950158119202},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6946624517440796},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6890056729316711},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5191646814346313},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5006554126739502},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.4569542407989502},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.45065778493881226},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4242130517959595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4150097668170929},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32819145917892456},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.21925082802772522},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco58844.2023.10289719","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/eusipco58844.2023.10289719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 31st European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2031993275","https://openalex.org/W2043415540","https://openalex.org/W2072506672","https://openalex.org/W2097156082","https://openalex.org/W2146744711","https://openalex.org/W2157770256","https://openalex.org/W2298692413","https://openalex.org/W2350054051","https://openalex.org/W2367043657","https://openalex.org/W2431637923","https://openalex.org/W2556806401","https://openalex.org/W2625898145","https://openalex.org/W2740222873","https://openalex.org/W2789243953","https://openalex.org/W2914703742","https://openalex.org/W2954377489","https://openalex.org/W2973122072","https://openalex.org/W2978589234","https://openalex.org/W3015266960","https://openalex.org/W3034679438","https://openalex.org/W3039756956","https://openalex.org/W3120599689","https://openalex.org/W3174351785","https://openalex.org/W4210484073","https://openalex.org/W4214865698","https://openalex.org/W4224281430","https://openalex.org/W4282036996","https://openalex.org/W4310970671","https://openalex.org/W4313366879","https://openalex.org/W4385245566","https://openalex.org/W6674697172","https://openalex.org/W6739901393","https://openalex.org/W6741771580","https://openalex.org/W6848703727"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2145836866","https://openalex.org/W2803255133","https://openalex.org/W4321789545"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,107],"consider":[4],"human":[5,105],"activity":[6],"recognition":[7],"with":[8,68,119],"a":[9,46,57,64,129],"semi-supervised":[10,58,125],"convolutional":[11],"autoencoder":[12],"(CAE),":[13],"augmented":[14],"by":[15],"an":[16,76],"attention":[17,87],"mechanism,":[18],"using":[19,79,94],"radar":[20],"micro-Doppler":[21],"signatures.":[22],"The":[23],"attention-augmented":[24],"CAE":[25],"(AA-CAE)":[26],"learns":[27],"both":[28,52],"global":[29],"information":[30],"and":[31,54,83,86],"spatially":[32],"localized":[33],"features,":[34],"thus":[35],"enabling":[36],"the":[37,41,71,84,91,96,110,124],"classifier":[38,85,114],"to":[39],"overcome":[40],"limited":[42],"receptive":[43],"field":[44],"of":[45,70,102],"CAE.":[47],"Considering":[48],"training":[49,59,69,81],"data":[50,122],"comprising":[51],"labeled":[53,97,121],"unlabeled":[55],"samples,":[56],"regime":[60],"is":[61],"implemented":[62],"through":[63],"joint":[65],"loss":[66],"function,":[67],"encoder":[72],"part":[73],"performed":[74],"in":[75],"unsupervised":[77],"fashion":[78],"all":[80],"samples":[82],"mechanism":[88],"trained":[89,112,127],"at":[90],"same":[92],"time":[93],"only":[95],"samples.":[98],"Using":[99],"real-data":[100],"measurements":[101],"six":[103],"different":[104],"activities,":[106],"demonstrate":[108],"that":[109],"jointly":[111],"AA-CAE":[113,126],"yields":[115],"higher":[116],"classification":[117],"accuracy":[118],"fewer":[120],"than":[123],"via":[128],"conventional":[130],"two-step":[131],"process.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
