{"id":"https://openalex.org/W4399770864","doi":"https://doi.org/10.1007/s11554-024-01496-8","title":"A generic deep learning architecture optimization method for edge device based on start-up latency reduction","display_name":"A generic deep learning architecture optimization method for edge device based on start-up latency reduction","publication_year":2024,"publication_date":"2024-06-18","ids":{"openalex":"https://openalex.org/W4399770864","doi":"https://doi.org/10.1007/s11554-024-01496-8"},"language":"en","primary_location":{"id":"doi:10.1007/s11554-024-01496-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11554-024-01496-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11554-024-01496-8.pdf","source":{"id":"https://openalex.org/S11282291","display_name":"Journal of Real-Time Image Processing","issn_l":"1861-8200","issn":["1861-8200","1861-8219"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Real-Time Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11554-024-01496-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010085152","display_name":"Qi Li","orcid":"https://orcid.org/0000-0002-1963-5263"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["College of Science and Engineering, Ritsumeikan University, Noji-higashi, Kusatsu, Shiga, 525-8577, Japan"],"affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Ritsumeikan University, Noji-higashi, Kusatsu, Shiga, 525-8577, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032417356","display_name":"Hengyi Li","orcid":"https://orcid.org/0000-0003-4112-7297"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hengyi Li","raw_affiliation_strings":["Research Organization of Science and Technology, Ritsumeikan University, Noji-higashi, Kusatsu, Shiga, 525-8577, Japan"],"affiliations":[{"raw_affiliation_string":"Research Organization of Science and Technology, Ritsumeikan University, Noji-higashi, Kusatsu, Shiga, 525-8577, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076579498","display_name":"Lin Meng","orcid":"https://orcid.org/0000-0003-4351-6923"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Lin Meng","raw_affiliation_strings":["Department of Electronic and Computer Engineering, Ritsumeikan University, Noji-higashi, Kusatsu, Shiga, 525-8577, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electronic and Computer Engineering, Ritsumeikan University, Noji-higashi, Kusatsu, Shiga, 525-8577, Japan","institution_ids":["https://openalex.org/I135768898"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076579498"],"corresponding_institution_ids":["https://openalex.org/I135768898"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.4478,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.81679636,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"21","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9983999729156494,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9983999729156494,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9896000027656555,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9891999959945679,"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/latency","display_name":"Latency (audio)","score":0.6872804164886475},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6705905795097351},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6351961493492126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6199389696121216},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.609815776348114},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5796355605125427},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.46048814058303833},{"id":"https://openalex.org/keywords/low-latency","display_name":"Low latency (capital markets)","score":0.4205603301525116},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4136275053024292},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20555540919303894},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14498218894004822},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13418379426002502},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.0696130096912384}],"concepts":[{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6872804164886475},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6705905795097351},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6351961493492126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6199389696121216},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.609815776348114},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5796355605125427},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.46048814058303833},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.4205603301525116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4136275053024292},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20555540919303894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14498218894004822},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13418379426002502},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0696130096912384},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s11554-024-01496-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11554-024-01496-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11554-024-01496-8.pdf","source":{"id":"https://openalex.org/S11282291","display_name":"Journal of Real-Time Image Processing","issn_l":"1861-8200","issn":["1861-8200","1861-8219"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Real-Time Image Processing","raw_type":"journal-article"},{"id":"pmh:oai:irdb.nii.ac.jp:01038:0006909189","is_oa":false,"landing_page_url":"https://ritsumei.repo.nii.ac.jp/records/2003661","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Real-Time Image Processing","raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.1007/s11554-024-01496-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11554-024-01496-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11554-024-01496-8.pdf","source":{"id":"https://openalex.org/S11282291","display_name":"Journal of Real-Time Image Processing","issn_l":"1861-8200","issn":["1861-8200","1861-8219"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Real-Time Image Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320318911","display_name":"KIOXIA Holdings Corporation","ror":null},{"id":"https://openalex.org/F4320323289","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399770864.pdf"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1782702917","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2783538964","https://openalex.org/W2889339831","https://openalex.org/W2907882680","https://openalex.org/W2928560789","https://openalex.org/W2946485102","https://openalex.org/W2963163009","https://openalex.org/W2970959587","https://openalex.org/W3007729836","https://openalex.org/W3008905965","https://openalex.org/W3014641619","https://openalex.org/W3034513523","https://openalex.org/W3034818206","https://openalex.org/W3035377608","https://openalex.org/W3035467254","https://openalex.org/W3080404596","https://openalex.org/W3099432326","https://openalex.org/W3159442541","https://openalex.org/W3172744943","https://openalex.org/W3185811833","https://openalex.org/W3193895134","https://openalex.org/W3208631787","https://openalex.org/W4200106037","https://openalex.org/W4206016550","https://openalex.org/W4220946453","https://openalex.org/W4281662450","https://openalex.org/W4287118909","https://openalex.org/W4324057834","https://openalex.org/W4381986098","https://openalex.org/W4384931412","https://openalex.org/W4386737313","https://openalex.org/W4386784351","https://openalex.org/W4387490275","https://openalex.org/W4389201177","https://openalex.org/W4389615706","https://openalex.org/W4390226880","https://openalex.org/W4390278368","https://openalex.org/W4390871752","https://openalex.org/W4391147412"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W3205411230","https://openalex.org/W4286899009","https://openalex.org/W9168048","https://openalex.org/W4300849822","https://openalex.org/W4376480820","https://openalex.org/W3155891479","https://openalex.org/W3029351463","https://openalex.org/W4308600690"],"abstract_inverted_index":{"Abstract":[0],"In":[1],"the":[2,68,91,167,189],"promising":[3],"Artificial":[4],"Intelligence":[5],"of":[6,70,104,141],"Things":[7],"technology,":[8],"deep":[9,23,41,114],"learning":[10,24,42,115],"algorithms":[11,25,43],"are":[12,26,60,151],"implemented":[13],"on":[14,44,73,83,106,123,153],"edge":[15,49,74,107,124,190],"devices":[16],"to":[17,36,67,87,119,173],"process":[18],"data":[19,88],"locally.":[20],"However,":[21],"high-performance":[22],"accompanied":[27],"by":[28,171],"increased":[29],"computation":[30],"and":[31,46,54,135,139,144,159,184],"parameter":[32],"storage":[33],"costs,":[34],"leading":[35],"difficulties":[37],"in":[38,97,130,188],"implementing":[39],"huge":[40],"memory":[45],"power":[47],"constrained":[48],"devices,":[50,75],"such":[51,62],"as":[52,63],"smartphones":[53],"drones.":[55],"Thus":[56],"various":[57],"compression":[58],"methods":[59,79],"proposed,":[61],"channel":[64,77,182],"pruning.":[65],"According":[66],"analysis":[69],"low-level":[71],"operations":[72],"existing":[76],"pruning":[78,140,183],"have":[80],"limited":[81],"effect":[82],"latency":[84,168],"optimization.":[85],"Due":[86],"processing":[89,103,187],"operations,":[90],"pruned":[92],"residual":[93,145],"blocks":[94,146],"still":[95],"result":[96],"significant":[98],"latency,":[99],"which":[100,175],"hinders":[101],"real-time":[102,186],"CNNs":[105],"devices.":[108,125],"Hence,":[109],"we":[110],"propose":[111],"a":[112],"generic":[113],"architecture":[116],"optimization":[117],"method":[118],"achieve":[120],"further":[121],"acceleration":[122],"The":[126,162],"network":[127],"is":[128,147,169,176],"optimized":[129],"two":[131],"stages,":[132],"Global":[133],"Constraint":[134],"Start-up":[136],"Latency":[137],"Reduction,":[138],"both":[142],"channels":[143],"achieved.":[148],"Optimized":[149],"networks":[150],"evaluated":[152],"desktop":[154],"CPU,":[155,158],"FPGA,":[156],"ARM":[157],"PULP":[160],"platforms.":[161],"experimental":[163],"results":[164],"show":[165],"that":[166],"reduced":[170],"up":[172],"70.40%,":[174],"13.63%":[177],"higher":[178],"than":[179],"only":[180],"applying":[181],"achieving":[185],"device.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}