{"id":"https://openalex.org/W3175064287","doi":"https://doi.org/10.1109/aicas51828.2021.9458487","title":"Quantized Fully Convolution Neural Network for HW Implementation of Human Posture Recognition","display_name":"Quantized Fully Convolution Neural Network for HW Implementation of Human Posture Recognition","publication_year":2021,"publication_date":"2021-06-06","ids":{"openalex":"https://openalex.org/W3175064287","doi":"https://doi.org/10.1109/aicas51828.2021.9458487","mag":"3175064287"},"language":"en","primary_location":{"id":"doi:10.1109/aicas51828.2021.9458487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas51828.2021.9458487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)","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/A5101985239","display_name":"Alessandro Russo","orcid":"https://orcid.org/0000-0002-4229-8293"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessandro Russo","raw_affiliation_strings":["University of Salerno, Fisciano, (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano, (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030070417","display_name":"Gian Domenico Licciardo","orcid":"https://orcid.org/0000-0002-1913-4928"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gian Domenico Licciardo","raw_affiliation_strings":["University of Salerno, Fisciano, (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano, (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026535044","display_name":"Luigi Di Benedetto","orcid":"https://orcid.org/0000-0001-5588-0621"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luigi Di Benedetto","raw_affiliation_strings":["University of Salerno, Fisciano, (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano, (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044628138","display_name":"Alfredo Rubino","orcid":"https://orcid.org/0000-0002-5690-9040"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alfredo Rubino","raw_affiliation_strings":["University of Salerno, Fisciano, (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano, (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029809556","display_name":"Rosalba Liguori","orcid":"https://orcid.org/0000-0002-0093-1169"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Rosalba Liguori","raw_affiliation_strings":["University of Salerno, Fisciano, (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano, (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008677280","display_name":"Alessandro Naddeo","orcid":"https://orcid.org/0000-0001-7728-4046"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessandro Naddeo","raw_affiliation_strings":["University of Salerno, Fisciano, (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano, (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066660127","display_name":"Nicola Cappetti","orcid":"https://orcid.org/0000-0002-5843-2805"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicola Cappetti","raw_affiliation_strings":["University of Salerno, Fisciano, (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Salerno, Fisciano, (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I131729948"],"apc_list":null,"apc_paid":null,"fwci":0.2864,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59064197,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.994700014591217,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.994700014591217,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9901999831199646,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.972599983215332,"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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8265764713287354},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.7319344282150269},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.7247787714004517},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7155216336250305},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6538028717041016},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6033392548561096},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5913805961608887},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4929961860179901},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.49130597710609436},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.474161297082901},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4299713373184204},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.38518020510673523},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.353746235370636},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.27170366048812866},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20393162965774536}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8265764713287354},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.7319344282150269},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.7247787714004517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7155216336250305},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6538028717041016},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6033392548561096},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5913805961608887},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4929961860179901},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.49130597710609436},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.474161297082901},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4299713373184204},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.38518020510673523},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.353746235370636},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27170366048812866},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20393162965774536},{"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/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aicas51828.2021.9458487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas51828.2021.9458487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1571463708","https://openalex.org/W1999879421","https://openalex.org/W2053460348","https://openalex.org/W2139436713","https://openalex.org/W2295107390","https://openalex.org/W2319920447","https://openalex.org/W2494745673","https://openalex.org/W2599135609","https://openalex.org/W2606699032","https://openalex.org/W2914492151","https://openalex.org/W2943916063","https://openalex.org/W2947898397","https://openalex.org/W2964007934","https://openalex.org/W3008684984","https://openalex.org/W3011842163","https://openalex.org/W3019215432","https://openalex.org/W3041090558","https://openalex.org/W3044894888","https://openalex.org/W3047171309","https://openalex.org/W3092256386","https://openalex.org/W3097855118","https://openalex.org/W6634078745","https://openalex.org/W6700264148"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W4386245174","https://openalex.org/W4200132709","https://openalex.org/W3198752256"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,9,54,69,84,107,123],"very":[4,70],"tiny":[5],"HW":[6],"design":[7,49,113],"of":[8,50,64,73,127,137,140],"Quantized":[10],"Fully":[11],"Convolutional":[12],"Neural":[13],"Network":[14],"is":[15],"proposed":[16],"which":[17],"demonstrates":[18],"that":[19],"accurate":[20],"Human":[21],"Posture":[22],"Recognition":[23],"can":[24],"be":[25],"designed":[26],"by":[27],"exploiting":[28],"only":[29],"pressure":[30],"sensors":[31,139],"and":[32,77,81,122],"keeping":[33],"the":[34,38,43,51,91,112,138],"computation":[35],"close":[36],"to":[37,42,58,97],"data":[39],"sources,":[40],"according":[41],"edge":[44],"computing":[45],"paradigm.":[46],"The":[47],"custom":[48],"QFCN":[52,92],"exploits":[53],"base-2":[55],"quantization":[56],"scheme":[57],"achieve":[59],"state-of-the-art":[60],"performances":[61],"in":[62,99],"terms":[63],"classification":[65],"accuracy,":[66],"together":[67],"with":[68,131],"reduced":[71],"number":[72],"mapped":[74],"physical":[75],"resources":[76],"power":[78,120],"consumption.":[79],"Trained":[80],"validated":[82],"on":[83,106],"public":[85],"dataset":[86],"for":[87],"in-bed":[88],"posture":[89],"classification,":[90],"exhibits":[93],"an":[94,132],"accuracy":[95],"up":[96],"96.77%":[98],"recognizing":[100],"17":[101],"different":[102],"postures.":[103],"When":[104],"prototyped":[105],"Xilinx":[108],"Artix":[109],"7":[110,117],"FPGA":[111],"achieves":[114],"less":[115],"than":[116],"mW":[118],"dynamic":[119],"dissipation":[121],"maximum":[124],"operation":[125],"frequency":[126],"26.6":[128],"MHz,":[129],"compatible":[130],"Output":[133],"Data":[134],"Rate":[135],"(ODR)":[136],"9.13":[141],"kHz.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
