{"id":"https://openalex.org/W3212555642","doi":"https://doi.org/10.3390/s21227529","title":"Evaluation of Deep Neural Network Compression Methods for Edge Devices Using Weighted Score-Based Ranking Scheme","display_name":"Evaluation of Deep Neural Network Compression Methods for Edge Devices Using Weighted Score-Based Ranking Scheme","publication_year":2021,"publication_date":"2021-11-12","ids":{"openalex":"https://openalex.org/W3212555642","doi":"https://doi.org/10.3390/s21227529","mag":"3212555642","pmid":"https://pubmed.ncbi.nlm.nih.gov/34833610"},"language":"en","primary_location":{"id":"doi:10.3390/s21227529","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21227529","pdf_url":"https://www.mdpi.com/1424-8220/21/22/7529/pdf?version=1636727873","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/1424-8220/21/22/7529/pdf?version=1636727873","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049599696","display_name":"Olutosin Ajibola Ademola","orcid":"https://orcid.org/0000-0002-4863-5422"},"institutions":[{"id":"https://openalex.org/I111112146","display_name":"Tallinn University of Technology","ror":"https://ror.org/0443cwa12","country_code":"EE","type":"education","lineage":["https://openalex.org/I111112146"]}],"countries":["EE"],"is_corresponding":true,"raw_author_name":"Olutosin Ajibola Ademola","raw_affiliation_strings":["Embedded AI Research Laboratory, Department of Computer Systems, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia"],"raw_orcid":"https://orcid.org/0000-0002-4863-5422","affiliations":[{"raw_affiliation_string":"Embedded AI Research Laboratory, Department of Computer Systems, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia","institution_ids":["https://openalex.org/I111112146"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038714483","display_name":"Mairo Leier","orcid":"https://orcid.org/0000-0002-9878-4477"},"institutions":[{"id":"https://openalex.org/I111112146","display_name":"Tallinn University of Technology","ror":"https://ror.org/0443cwa12","country_code":"EE","type":"education","lineage":["https://openalex.org/I111112146"]}],"countries":["EE"],"is_corresponding":false,"raw_author_name":"Mairo Leier","raw_affiliation_strings":["Embedded AI Research Laboratory, Department of Computer Systems, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia"],"raw_orcid":"https://orcid.org/0000-0002-9878-4477","affiliations":[{"raw_affiliation_string":"Embedded AI Research Laboratory, Department of Computer Systems, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia","institution_ids":["https://openalex.org/I111112146"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061791014","display_name":"Eduard Petlenkov","orcid":"https://orcid.org/0000-0003-2167-6280"},"institutions":[{"id":"https://openalex.org/I111112146","display_name":"Tallinn University of Technology","ror":"https://ror.org/0443cwa12","country_code":"EE","type":"education","lineage":["https://openalex.org/I111112146"]}],"countries":["EE"],"is_corresponding":false,"raw_author_name":"Eduard Petlenkov","raw_affiliation_strings":["Centre for Intelligent Systems, Department of Computer Systems, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia"],"raw_orcid":"https://orcid.org/0000-0003-2167-6280","affiliations":[{"raw_affiliation_string":"Centre for Intelligent Systems, Department of Computer Systems, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia","institution_ids":["https://openalex.org/I111112146"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049599696"],"corresponding_institution_ids":["https://openalex.org/I111112146"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.9698,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78005165,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"21","issue":"22","first_page":"7529","last_page":"7529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9916999936103821,"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/T12676","display_name":"Machine Learning and ELM","score":0.9905999898910522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7555041909217834},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6102218627929688},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5946080684661865},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5920664668083191},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5736368894577026},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.5444158315658569},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5280571579933167},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5238468647003174},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5176997184753418},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.501061201095581},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3592938780784607},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.345718115568161},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1963706910610199},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12061011791229248}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7555041909217834},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6102218627929688},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5946080684661865},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5920664668083191},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5736368894577026},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.5444158315658569},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5280571579933167},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5238468647003174},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5176997184753418},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.501061201095581},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3592938780784607},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.345718115568161},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1963706910610199},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12061011791229248},{"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/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.0},{"id":"https://openalex.org/C511840579","wikidata":"https://www.wikidata.org/wiki/Q12757","display_name":"Internal combustion engine","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D011312","descriptor_name":"Pressure","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011312","descriptor_name":"Pressure","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011312","descriptor_name":"Pressure","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":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":"D044962","descriptor_name":"Data Compression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s21227529","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21227529","pdf_url":"https://www.mdpi.com/1424-8220/21/22/7529/pdf?version=1636727873","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:34833610","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34833610","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:348a22621e7447a08b4c016aa14abe64","is_oa":true,"landing_page_url":"https://doaj.org/article/348a22621e7447a08b4c016aa14abe64","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 21, Iss 22, p 7529 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/22/7529/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21227529","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 21; Issue 22; Pages: 7529","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8622199","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8622199","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/s21227529","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21227529","pdf_url":"https://www.mdpi.com/1424-8220/21/22/7529/pdf?version=1636727873","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3212555642.pdf","grobid_xml":"https://content.openalex.org/works/W3212555642.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1533026269","https://openalex.org/W1845051632","https://openalex.org/W1902934009","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2104948848","https://openalex.org/W2134273960","https://openalex.org/W2145085734","https://openalex.org/W2167215970","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2294370754","https://openalex.org/W2300242332","https://openalex.org/W2417429787","https://openalex.org/W2549401308","https://openalex.org/W2783318359","https://openalex.org/W2804935370","https://openalex.org/W2884367402","https://openalex.org/W2905307300","https://openalex.org/W2963125010","https://openalex.org/W2963273111","https://openalex.org/W2964350391","https://openalex.org/W2971170030","https://openalex.org/W2999093589","https://openalex.org/W2999629881","https://openalex.org/W3004127093","https://openalex.org/W3008684984","https://openalex.org/W3202442802","https://openalex.org/W6747544394"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2188500270","https://openalex.org/W2303858293","https://openalex.org/W2915512527","https://openalex.org/W2798198862","https://openalex.org/W51364034","https://openalex.org/W2798997222","https://openalex.org/W4386245174","https://openalex.org/W4200132709","https://openalex.org/W3198752256"],"abstract_inverted_index":{"The":[0,140],"demand":[1],"for":[2,16,52,100,151,187,195],"object":[3,22],"detection":[4,23],"capability":[5],"in":[6,34,38,198],"edge":[7,39,196],"computing":[8],"systems":[9],"has":[10,25],"surged.":[11],"As":[12],"such,":[13],"the":[14,46,53,66,79,115,121,130,146,152,155,188],"need":[15,48],"lightweight":[17],"Convolutional":[18],"Neural":[19],"Network":[20],"(CNN)-based":[21],"models":[24,31,47,135],"become":[26],"a":[27,88,95,108,185],"focal":[28],"point.":[29],"Current":[30],"are":[32],"large":[33],"memory":[35],"and":[36,133,180],"deployment":[37],"devices":[40,197],"is":[41,70,145,178],"demanding.":[42],"This":[43],"shows":[44],"that":[45,113,143],"to":[49,77,93],"be":[50,182],"optimized":[51],"hardware":[54],"without":[55],"performance":[56,80,117],"degradation.":[57],"There":[58],"exist":[59],"several":[60],"model":[61,116,192],"compression":[62,149,193],"methods;":[63],"however,":[64],"determining":[65],"most":[67,147],"efficient":[68,148],"method":[69,125,150,177],"of":[71,81,123,163,173,190],"major":[72],"concern.":[73],"Our":[74,175],"goal":[75],"was":[76],"rank":[78],"these":[82],"methods":[83,194],"using":[84],"our":[85,138],"application":[86],"as":[87,184],"case":[89],"study.":[90],"We":[91,119],"aimed":[92],"develop":[94],"real-time":[96],"vehicle":[97],"tracking":[98],"system":[99],"cargo":[101],"ships.":[102],"To":[103],"address":[104],"this,":[105],"we":[106],"developed":[107],"weighted":[109,161,171],"score-based":[110],"ranking":[111],"scheme":[112],"utilizes":[114],"metrics.":[118],"demonstrated":[120],"effectiveness":[122],"this":[124],"by":[126,166],"applying":[127],"it":[128],"on":[129,137],"baseline,":[131],"compressed,":[132],"micro-CNN":[134],"trained":[136],"dataset.":[139],"result":[141],"showed":[142],"quantization":[144],"application,":[153],"having":[154,168],"highest":[156],"rank,":[157],"with":[158],"an":[159,169],"average":[160,170],"score":[162,172],"9.00,":[164],"followed":[165],"binarization,":[167],"8.07.":[174],"proposed":[176],"extendable":[179],"can":[181],"used":[183],"framework":[186],"selection":[189],"suitable":[191],"different":[199],"applications.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}