{"id":"https://openalex.org/W4281262639","doi":"https://doi.org/10.3390/s22103898","title":"An Infrared Array Sensor-Based Approach for Activity Detection, Combining Low-Cost Technology with Advanced Deep Learning Techniques","display_name":"An Infrared Array Sensor-Based Approach for Activity Detection, Combining Low-Cost Technology with Advanced Deep Learning Techniques","publication_year":2022,"publication_date":"2022-05-20","ids":{"openalex":"https://openalex.org/W4281262639","doi":"https://doi.org/10.3390/s22103898","pmid":"https://pubmed.ncbi.nlm.nih.gov/35632305"},"language":"en","primary_location":{"id":"doi:10.3390/s22103898","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22103898","pdf_url":"https://www.mdpi.com/1424-8220/22/10/3898/pdf?version=1653353348","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/10/3898/pdf?version=1653353348","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041242688","display_name":"K. Muthukumar","orcid":"https://orcid.org/0000-0002-7923-3995"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Krishnan Arumugasamy Muthukumar","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University, Yokohama 223-8522, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University, Yokohama 223-8522, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068994330","display_name":"Mondher Bouazizi","orcid":"https://orcid.org/0000-0001-7055-9318"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mondher Bouazizi","raw_affiliation_strings":["Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016337773","display_name":"Tomoaki Ohtsuki","orcid":"https://orcid.org/0000-0003-3961-1426"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tomoaki Ohtsuki","raw_affiliation_strings":["Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016337773"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.2236,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.79954889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"22","issue":"10","first_page":"3898","last_page":"3898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9929999709129333,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9929999709129333,"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":0.9927999973297119,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7863287925720215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7772716283798218},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7516341209411621},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7419594526290894},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5413647890090942},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.519011378288269},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5081443786621094},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4334174394607544},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34511110186576843},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20917421579360962}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7863287925720215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7772716283798218},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7516341209411621},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7419594526290894},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5413647890090942},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.519011378288269},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5081443786621094},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4334174394607544},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34511110186576843},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20917421579360962}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D013672","descriptor_name":"Technology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013672","descriptor_name":"Technology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013672","descriptor_name":"Technology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22103898","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22103898","pdf_url":"https://www.mdpi.com/1424-8220/22/10/3898/pdf?version=1653353348","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:35632305","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35632305","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:fe41fc82b6474151b0232be4f2b50153","is_oa":true,"landing_page_url":"https://doaj.org/article/fe41fc82b6474151b0232be4f2b50153","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 10, p 3898 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/10/3898/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22103898","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Sensors; Volume 22; Issue 10; Pages: 3898","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9145665","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9145665","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22103898","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22103898","pdf_url":"https://www.mdpi.com/1424-8220/22/10/3898/pdf?version=1653353348","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4000000059604645}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320909","display_name":"Keio University","ror":"https://ror.org/02kn6nx58"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4281262639.pdf","grobid_xml":"https://content.openalex.org/works/W4281262639.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1547647072","https://openalex.org/W1605510164","https://openalex.org/W1901129140","https://openalex.org/W2170939901","https://openalex.org/W2194775991","https://openalex.org/W2503339013","https://openalex.org/W2568603817","https://openalex.org/W2898486367","https://openalex.org/W2898720971","https://openalex.org/W2913106141","https://openalex.org/W2956015785","https://openalex.org/W2963122961","https://openalex.org/W3007117763","https://openalex.org/W3007175960","https://openalex.org/W3027391820","https://openalex.org/W3047450415","https://openalex.org/W3082833301","https://openalex.org/W3091812344","https://openalex.org/W3093993765","https://openalex.org/W3109853268","https://openalex.org/W3121320991","https://openalex.org/W3166075483","https://openalex.org/W3169893408","https://openalex.org/W3197817011","https://openalex.org/W3213023270","https://openalex.org/W4200388355","https://openalex.org/W4220847164","https://openalex.org/W4221102521","https://openalex.org/W4312632522","https://openalex.org/W6746466744","https://openalex.org/W6763278908"],"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/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4367628250","https://openalex.org/W3034789145","https://openalex.org/W4388819787"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,158,206],"propose":[4],"an":[5],"activity":[6],"detection":[7],"system":[8],"using":[9,76,131],"a":[10,77,83,89,108,121,173],"24":[11,31],"\u00d7":[12,32,35,39,190,202],"32":[13],"resolution":[14],"infrared":[15,169],"array":[16],"sensor":[17],"placed":[18],"on":[19,69],"the":[20,25,43,56,59,64,70,72,100,103,129,134,149,153,208],"ceiling.":[21],"We":[22,61,94],"first":[23],"collect":[24],"data":[26,96,116,142],"at":[27],"different":[28],"resolutions":[29],"(i.e.,":[30],"32,":[33],"12":[34,201],"16,":[36],"and":[37,41,52,88,136,193,210],"6":[38,189],"8)":[40],"apply":[42],"advanced":[44],"deep":[45,79,163],"learning":[46,80,164],"(DL)":[47],"techniques":[48,165],"of":[49,58,66,102,111,115,152],"Super-Resolution":[50],"(SR)":[51],"denoising":[53],"to":[54,98,147,166,172,184,196],"enhance":[55],"quality":[57],"images.":[60],"then":[62],"classify":[63],"images/sequences":[65],"images":[67,130,170,187,199],"depending":[68],"activities":[71],"subject":[73],"is":[74,118,146],"performing":[75],"hybrid":[78],"model":[81],"combining":[82],"Convolutional":[84],"Neural":[85],"Network":[86,125],"(CNN)":[87],"Long":[90],"Short-Term":[91],"Memory":[92],"(LSTM).":[93],"use":[95],"augmentation":[97,117],"improve":[99,148],"training":[101,139],"neural":[104,154],"networks":[105],"by":[106,120],"incorporating":[107],"wider":[109],"variety":[110],"samples.":[112],"The":[113,178],"process":[114],"performed":[119],"Conditional":[122],"Generative":[123],"Adversarial":[124],"(CGAN).":[126],"By":[127],"enhancing":[128],"SR,":[132],"removing":[133],"noise,":[135],"adding":[137],"more":[138],"samples":[140],"via":[141],"augmentation,":[143],"our":[144],"target":[145],"classification":[150,179],"accuracy":[151,180],"network.":[155],"Through":[156],"experiments,":[157],"show":[159],"that":[160],"employing":[161],"these":[162],"low-resolution":[167],"noisy":[168],"leads":[171],"noticeable":[174],"improvement":[175],"in":[176],"performance.":[177],"improved":[181],"from":[182,194],"78.32%":[183],"84.43%":[185],"(for":[186,198],"with":[188,200],"8":[191],"resolution),":[192],"90.11%":[195],"94.54%":[197],"16":[203],"resolution)":[204],"when":[205],"used":[207],"CNN":[209,211],"+":[212],"LSTM":[213],"networks,":[214],"respectively.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
