{"id":"https://openalex.org/W2909981485","doi":"https://doi.org/10.3390/make1010027","title":"Guidelines and Benchmarks for Deployment of Deep Learning Models on Smartphones as Real-Time Apps","display_name":"Guidelines and Benchmarks for Deployment of Deep Learning Models on Smartphones as Real-Time Apps","publication_year":2019,"publication_date":"2019-02-13","ids":{"openalex":"https://openalex.org/W2909981485","doi":"https://doi.org/10.3390/make1010027","mag":"2909981485"},"language":"en","primary_location":{"id":"doi:10.3390/make1010027","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1010027","pdf_url":"https://www.mdpi.com/2504-4990/1/1/27/pdf?version=1550078393","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/1/1/27/pdf?version=1550078393","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020085415","display_name":"Abhishek Sehgal","orcid":"https://orcid.org/0000-0001-7128-6438"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhishek Sehgal","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX 75080, USA"],"raw_orcid":"https://orcid.org/0000-0001-7128-6438","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX 75080, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076371436","display_name":"Nasser Kehtarnavaz","orcid":"https://orcid.org/0000-0001-5183-6359"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nasser Kehtarnavaz","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX 75080, USA"],"raw_orcid":"https://orcid.org/0000-0001-5183-6359","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX 75080, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5020085415"],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":2.757,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.9242386,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"1","issue":"1","first_page":"450","last_page":"465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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":0.9980999827384949,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9958999752998352,"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/deep-learning","display_name":"Deep learning","score":0.8205409646034241},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8087651133537292},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.7553910613059998},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7181369066238403},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5954596996307373},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5543411374092102},{"id":"https://openalex.org/keywords/android","display_name":"Android (operating system)","score":0.5532205700874329},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5082990527153015},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.48961859941482544},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.47563910484313965},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.462974488735199},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.40519726276397705},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3258533477783203},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.2591390013694763},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.20286774635314941}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.8205409646034241},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8087651133537292},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.7553910613059998},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7181369066238403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5954596996307373},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5543411374092102},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.5532205700874329},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5082990527153015},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.48961859941482544},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.47563910484313965},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.462974488735199},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.40519726276397705},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3258533477783203},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.2591390013694763},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.20286774635314941},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make1010027","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1010027","pdf_url":"https://www.mdpi.com/2504-4990/1/1/27/pdf?version=1550078393","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:mdpi.com:/2504-4990/1/1/27/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/make1010027","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":"Machine Learning and Knowledge Extraction","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/make1010027","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1010027","pdf_url":"https://www.mdpi.com/2504-4990/1/1/27/pdf?version=1550078393","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2909981485.pdf","grobid_xml":"https://content.openalex.org/works/W2909981485.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1984541135","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2141504882","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2739601332","https://openalex.org/W2755569691","https://openalex.org/W2792351646","https://openalex.org/W2919115771","https://openalex.org/W2963446712","https://openalex.org/W4236853429"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2112883198"],"abstract_inverted_index":{"Deep":[0],"learning":[1,22,53,70,124,140],"solutions":[2,44],"are":[3,12,25,59,167],"being":[4],"increasingly":[5],"used":[6,60],"in":[7,28,31,61],"mobile":[8],"applications.":[9],"Although":[10],"there":[11,24],"many":[13],"open-source":[14],"software":[15,143],"tools":[16,38],"for":[17,35,82,115],"the":[18,48,55,159,164],"development":[19],"of":[20,42,50,68,78,90,106],"deep":[21,52,69,123,139],"solutions,":[23],"no":[26],"guidelines":[27],"one":[29],"place":[30],"a":[32],"unified":[33],"manner":[34],"using":[36,91],"these":[37,43],"toward":[39],"real-time":[40,66,97,111,130],"deployment":[41,67,120],"on":[45,73,136,163],"smartphones.":[46,74,87],"From":[47],"variety":[49],"available":[51,138],"tools,":[54],"most":[56],"suited":[57],"ones":[58],"this":[62],"paper":[63],"to":[64,93,126,149],"enable":[65],"inference":[71],"networks":[72],"A":[75,102],"uniform":[76],"flow":[77],"implementation":[79],"is":[80,99,113,147],"devised":[81],"both":[83],"Android":[84],"and":[85,110,141,158],"iOS":[86],"The":[88,118],"advantage":[89],"multi-threading":[92],"achieve":[94],"or":[95,152],"improve":[96],"throughputs":[98],"also":[100],"showcased.":[101],"benchmarking":[103,165],"framework":[104],"consisting":[105],"accuracy,":[107],"CPU/GPU":[108],"consumption,":[109],"throughput":[112],"considered":[114],"validation":[116,160],"purposes.":[117],"developed":[119],"approach":[121,146],"allows":[122],"models":[125],"be":[127],"turned":[128],"into":[129],"smartphone":[131,142],"apps":[132],"with":[133],"ease":[134],"based":[135,162],"publicly":[137],"tools.":[144],"This":[145],"applied":[148],"six":[150],"popular":[151],"representative":[153],"convolutional":[154],"neural":[155],"network":[156],"models,":[157],"results":[161],"metrics":[166],"reported.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
