{"id":"https://openalex.org/W4206746514","doi":"https://doi.org/10.3390/s22020473","title":"Neural Fourier Energy Disaggregation","display_name":"Neural Fourier Energy Disaggregation","publication_year":2022,"publication_date":"2022-01-09","ids":{"openalex":"https://openalex.org/W4206746514","doi":"https://doi.org/10.3390/s22020473","pmid":"https://pubmed.ncbi.nlm.nih.gov/35062434"},"language":"en","primary_location":{"id":"doi:10.3390/s22020473","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22020473","pdf_url":"https://www.mdpi.com/1424-8220/22/2/473/pdf?version=1642060031","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/1424-8220/22/2/473/pdf?version=1642060031","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053932504","display_name":"Christoforos Nalmpantis","orcid":"https://orcid.org/0000-0002-7398-5862"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Christoforos Nalmpantis","raw_affiliation_strings":["School of Informatics, Aristotle University of Thessaloniki, 54124 Thesssaloniki, Greece"],"raw_orcid":"https://orcid.org/0000-0002-7398-5862","affiliations":[{"raw_affiliation_string":"School of Informatics, Aristotle University of Thessaloniki, 54124 Thesssaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036461243","display_name":"Nikolaos Virtsionis Gkalinikis","orcid":"https://orcid.org/0000-0002-3043-9220"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikolaos Virtsionis Gkalinikis","raw_affiliation_strings":["School of Informatics, Aristotle University of Thessaloniki, 54124 Thesssaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics, Aristotle University of Thessaloniki, 54124 Thesssaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009998024","display_name":"Dimitris Vrakas","orcid":"https://orcid.org/0000-0001-8559-6269"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitris Vrakas","raw_affiliation_strings":["School of Informatics, Aristotle University of Thessaloniki, 54124 Thesssaloniki, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics, Aristotle University of Thessaloniki, 54124 Thesssaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5053932504"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":1.8627,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.84986006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"22","issue":"2","first_page":"473","last_page":"473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10603","display_name":"Smart Grid Energy Management","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9769999980926514,"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/computer-science","display_name":"Computer science","score":0.7407300472259521},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.731529712677002},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7024335861206055},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6799659132957458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6322295665740967},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6284617185592651},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5725351572036743},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4974370300769806},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.47773855924606323},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.46492815017700195},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4306448698043823},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4108165502548218},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14240789413452148},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06608200073242188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7407300472259521},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.731529712677002},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7024335861206055},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6799659132957458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6322295665740967},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6284617185592651},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5725351572036743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4974370300769806},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.47773855924606323},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.46492815017700195},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4306448698043823},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4108165502548218},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14240789413452148},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06608200073242188},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055585","descriptor_name":"Physical Phenomena","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055585","descriptor_name":"Physical Phenomena","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055585","descriptor_name":"Physical Phenomena","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055585","descriptor_name":"Physical Phenomena","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22020473","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22020473","pdf_url":"https://www.mdpi.com/1424-8220/22/2/473/pdf?version=1642060031","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:35062434","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35062434","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:88d282badfb34f299ec70d8cf888e70f","is_oa":true,"landing_page_url":"https://doaj.org/article/88d282badfb34f299ec70d8cf888e70f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 22, Iss 2, p 473 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/2/473/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22020473","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 2; Pages: 473","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8779842","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8779842","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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/s22020473","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22020473","pdf_url":"https://www.mdpi.com/1424-8220/22/2/473/pdf?version=1642060031","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":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8899999856948853}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206746514.pdf","grobid_xml":"https://content.openalex.org/works/W4206746514.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1479651931","https://openalex.org/W1996944908","https://openalex.org/W2095705004","https://openalex.org/W2097481773","https://openalex.org/W2123910460","https://openalex.org/W2133564696","https://openalex.org/W2157331557","https://openalex.org/W2237952612","https://openalex.org/W2292311507","https://openalex.org/W2465358378","https://openalex.org/W2566212894","https://openalex.org/W2784248148","https://openalex.org/W2861817451","https://openalex.org/W2897481878","https://openalex.org/W2903902573","https://openalex.org/W2940200204","https://openalex.org/W2946668189","https://openalex.org/W2971067036","https://openalex.org/W2984293231","https://openalex.org/W2990279883","https://openalex.org/W2991526275","https://openalex.org/W3015396216","https://openalex.org/W3021704418","https://openalex.org/W3022078741","https://openalex.org/W3034573343","https://openalex.org/W3095865977","https://openalex.org/W3099873379","https://openalex.org/W3102977103","https://openalex.org/W3107101618","https://openalex.org/W3107922427","https://openalex.org/W3108696419","https://openalex.org/W3119642604","https://openalex.org/W3127962484","https://openalex.org/W3128916140","https://openalex.org/W3129106477","https://openalex.org/W3131561238","https://openalex.org/W3155660003","https://openalex.org/W3162090017","https://openalex.org/W3163514138","https://openalex.org/W3187780006","https://openalex.org/W3203623310","https://openalex.org/W3208170505","https://openalex.org/W3216275531","https://openalex.org/W6674330103","https://openalex.org/W6739901393","https://openalex.org/W6771626834","https://openalex.org/W6783944145","https://openalex.org/W6963387874"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291","https://openalex.org/W2363545964"],"abstract_inverted_index":{"Deploying":[0],"energy":[1],"disaggregation":[2],"models":[3,12,38],"in":[4],"the":[5,30,50,54,108],"real-world":[6],"is":[7,65,107],"a":[8,25,57,67,73],"challenging":[9],"task.":[10,69],"These":[11],"are":[13,39],"usually":[14,40],"deep":[15],"neural":[16,58,75],"networks":[17],"and":[18,43,53,84,116],"can":[19,118],"be":[20,119],"costly":[21],"when":[22,29],"running":[23],"on":[24,96],"server":[26],"or":[27],"prohibitive":[28],"target":[31],"device":[32],"has":[33,78,112],"limited":[34],"resources.":[35],"Deep":[36],"learning":[37,80,114],"computationally":[41],"expensive":[42],"they":[44],"have":[45],"large":[46],"storage":[47],"requirements.":[48],"Reducing":[49],"computational":[51],"cost":[52],"size":[55,83],"of":[56],"network,":[59],"without":[60,88],"trading":[61,89],"off":[62,90],"any":[63],"performance":[64],"not":[66],"trivial":[68],"This":[70],"paper":[71],"suggests":[72],"novel":[74],"architecture":[76,94],"that":[77],"less":[79],"parameters,":[81],"smaller":[82],"fast":[85],"inference":[86],"time":[87],"performance.":[91],"The":[92,104],"proposed":[93],"performs":[95],"par":[97],"with":[98],"two":[99],"popular":[100],"strong":[101],"baseline":[102],"models.":[103],"key":[105],"characteristic":[106],"Fourier":[109],"transformation":[110],"which":[111],"no":[113],"parameters":[115],"it":[117],"computed":[120],"efficiently.":[121]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
