{"id":"https://openalex.org/W4309242452","doi":"https://doi.org/10.1109/biocas54905.2022.9948676","title":"Aggressively prunable MAM\u00b2-based Deep Neural Oracle for ECG acquisition by Compressed Sensing","display_name":"Aggressively prunable MAM\u00b2-based Deep Neural Oracle for ECG acquisition by Compressed Sensing","publication_year":2022,"publication_date":"2022-10-13","ids":{"openalex":"https://openalex.org/W4309242452","doi":"https://doi.org/10.1109/biocas54905.2022.9948676"},"language":"en","primary_location":{"id":"doi:10.1109/biocas54905.2022.9948676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas54905.2022.9948676","pdf_url":null,"source":{"id":"https://openalex.org/S4363608179","display_name":"2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5065084602","display_name":"Philippe Bich","orcid":"https://orcid.org/0000-0001-9011-7437"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Philippe Bich","raw_affiliation_strings":["Politecnico di Torino,DET,Italy","DET, Politecnico di Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"DET, Politecnico di Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032387854","display_name":"Luciano Prono","orcid":"https://orcid.org/0000-0003-1507-9092"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luciano Prono","raw_affiliation_strings":["Politecnico di Torino,DET,Italy","DET, Politecnico di Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"DET, Politecnico di Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081473165","display_name":"Mauro Mangia","orcid":"https://orcid.org/0000-0002-3818-9115"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mauro Mangia","raw_affiliation_strings":["University of Bologna,DEI,Italy","DEI, University of Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bologna,DEI,Italy","institution_ids":["https://openalex.org/I9360294"]},{"raw_affiliation_string":"DEI, University of Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019602694","display_name":"Fabio Pareschi","orcid":"https://orcid.org/0000-0001-8777-7135"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]},{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Pareschi","raw_affiliation_strings":["Politecnico di Torino,DET,Italy","ARCES, University of Bologna, Italy","DET, Politecnico di Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"ARCES, University of Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]},{"raw_affiliation_string":"DET, Politecnico di Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088876922","display_name":"Riccardo Rovatti","orcid":"https://orcid.org/0000-0002-4731-7860"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Riccardo Rovatti","raw_affiliation_strings":["University of Bologna,DEI,Italy","ARCES, University of Bologna, Italy","DEI, University of Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bologna,DEI,Italy","institution_ids":["https://openalex.org/I9360294"]},{"raw_affiliation_string":"ARCES, University of Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]},{"raw_affiliation_string":"DEI, University of Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062714455","display_name":"Gianluca Setti","orcid":"https://orcid.org/0000-0002-2496-1856"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]},{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gianluca Setti","raw_affiliation_strings":["Politecnico di Torino,DET,Italy","ARCES, University of Bologna, Italy","DET, Politecnico di Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DET,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"ARCES, University of Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]},{"raw_affiliation_string":"DET, Politecnico di Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9823,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.9210091,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"163","last_page":"167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.9994999766349792,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8209751844406128},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7148551344871521},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.6793742179870605},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.6073004603385925},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5950571298599243},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5721756219863892},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5470196008682251},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5063298940658569},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4683961868286133},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.46072912216186523},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3793303370475769},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3788030445575714},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3474469482898712}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8209751844406128},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7148551344871521},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.6793742179870605},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.6073004603385925},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5950571298599243},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5721756219863892},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5470196008682251},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5063298940658569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4683961868286133},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.46072912216186523},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3793303370475769},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3788030445575714},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3474469482898712},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"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/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/biocas54905.2022.9948676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas54905.2022.9948676","pdf_url":null,"source":{"id":"https://openalex.org/S4363608179","display_name":"2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.unibo.it:11585/907420","is_oa":false,"landing_page_url":"https://hdl.handle.net/11585/907420","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1972967427","https://openalex.org/W2013024221","https://openalex.org/W2065581062","https://openalex.org/W2083042020","https://openalex.org/W2127271355","https://openalex.org/W2131496831","https://openalex.org/W2132904166","https://openalex.org/W2145096794","https://openalex.org/W2166670884","https://openalex.org/W2219727625","https://openalex.org/W2273561594","https://openalex.org/W2289917018","https://openalex.org/W2507344106","https://openalex.org/W2578009003","https://openalex.org/W2798559986","https://openalex.org/W2805003733","https://openalex.org/W2896409484","https://openalex.org/W2921746183","https://openalex.org/W2963363373","https://openalex.org/W2963828549","https://openalex.org/W2964178808","https://openalex.org/W2964251511","https://openalex.org/W2983605412","https://openalex.org/W3017895246","https://openalex.org/W3089699294","https://openalex.org/W3102722370","https://openalex.org/W3107308437","https://openalex.org/W4250955649","https://openalex.org/W4313150396","https://openalex.org/W6631190155","https://openalex.org/W6745499552","https://openalex.org/W6751979845","https://openalex.org/W6755843862"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W3110702597","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W2073713056","https://openalex.org/W1881631164","https://openalex.org/W2125620709","https://openalex.org/W2964217848","https://openalex.org/W3017872546"],"abstract_inverted_index":{"The":[0,153],"growing":[1],"interest":[2],"in":[3,95,123],"Internet":[4],"of":[5,48,64,107,120,172,192,198],"Things":[6],"(IoT)":[7],"and":[8,46,97,113,132,143,158,177],"mobile":[9],"biomedical":[10],"applications":[11],"is":[12,33,87,151,155,166,180],"pushing":[13],"the":[14,24,40,44,53,56,62,90,105,139,147,170,189,193,199],"investigation":[15],"on":[16,82],"approaches":[17],"that":[18,36,74,102],"can":[19,103,118],"be":[20,80,119],"used":[21,167],"to":[22,38,55,79,93,168],"reduce":[23,39,104,169],"energy":[25,41],"consumption":[26],"while":[27],"acquiring":[28],"data.":[29],"Compressed":[30],"Sensing":[31],"(CS)":[32],"a":[34,49,83,129,156,173],"technique":[35,142],"allows":[37],"required":[42],"for":[43,69,89],"acquisition":[45],"compression":[47],"sparse":[50],"signal,":[51],"transferring":[52],"complexity":[54,171],"reconstruction":[57,71],"stage.":[58],"Many":[59],"works":[60],"leverage":[61],"use":[63],"Deep":[65],"Neural":[66],"Networks":[67],"(DNNs)":[68],"signal":[70],"and,":[72],"assuming":[73],"also":[75],"this":[76,124,127],"operation":[77],"has":[78],"performed":[81],"IoT":[84],"device,":[85],"it":[86],"necessary":[88],"DNN":[91,161],"architecture":[92],"fit":[94],"small":[96],"low-energy":[98],"devices.":[99],"Pruning":[100],"techniques,":[101],"size":[106],"DNNs":[108],"by":[109],"removing":[110],"unnecessary":[111],"parameters":[112,200],"thus":[114],"decreasing":[115],"storage":[116],"requirements,":[117],"great":[121],"help":[122],"effort.":[125],"In":[126],"work,":[128],"novel":[130],"Multiply":[131],"Max&Min":[133],"(MAM\u00b2)":[134],"map-reduce":[135],"paradigm":[136],"trained":[137],"with":[138,146,196],"vanishing":[140],"contributes":[141],"then":[144],"pruned":[145,160,201],"activation":[148],"rate":[149],"method":[150],"proposed.":[152],"result":[154],"naturally":[157],"aggressively":[159],"layer":[162],"structure.":[163],"This":[164],"structure":[165],"DNN-based":[174],"CS":[175,194],"reconstructor":[176],"its":[178],"performance":[179],"verified.":[181],"As":[182],"an":[183],"example,":[184],"MAM\u00b2-based":[185],"layers":[186,208],"still":[187],"retain":[188],"baseline":[190],"accuracy":[191],"decoder":[195],"94%":[197],"against":[202],"25%":[203],"when":[204],"using":[205],"classic":[206],"MAC-based":[207],"only.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}