{"id":"https://openalex.org/W4403277194","doi":"https://doi.org/10.1109/tits.2024.3419095","title":"Differential Image-Based Scalable YOLOv7-Tiny Implementation for Clustered Embedded Systems","display_name":"Differential Image-Based Scalable YOLOv7-Tiny Implementation for Clustered Embedded Systems","publication_year":2024,"publication_date":"2024-10-09","ids":{"openalex":"https://openalex.org/W4403277194","doi":"https://doi.org/10.1109/tits.2024.3419095"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3419095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3419095","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","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/A5074116974","display_name":"Sung\u2010Hoon Hong","orcid":"https://orcid.org/0000-0002-3408-2820"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Sunghoon Hong","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030304824","display_name":"Daejin Park","orcid":"https://orcid.org/0000-0002-5560-873X"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daejin Park","raw_affiliation_strings":["School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074116974"],"corresponding_institution_ids":["https://openalex.org/I31419693"],"apc_list":null,"apc_paid":null,"fwci":0.6985,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74525726,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"25","issue":"11","first_page":"16036","last_page":"16047"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8910999894142151,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8910999894142151,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6447088718414307},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5864589810371399},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3617863655090332},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3536335229873657},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34477341175079346},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.0910557210445404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6447088718414307},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5864589810371399},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3617863655090332},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3536335229873657},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34477341175079346},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0910557210445404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3419095","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3419095","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2584457256","display_name":null,"funder_award_id":"NRF-2018R1A6A1A03025109","funder_id":"https://openalex.org/F4320311687","funder_display_name":"Ministry of Education"},{"id":"https://openalex.org/G5366787154","display_name":null,"funder_award_id":"NRF-2022R1I1A3069260","funder_id":"https://openalex.org/F4320311687","funder_display_name":"Ministry of Education"}],"funders":[{"id":"https://openalex.org/F4320311687","display_name":"Ministry of Education","ror":"https://ror.org/03m01yf64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W1988888548","https://openalex.org/W2102605133","https://openalex.org/W2147076738","https://openalex.org/W2172654076","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2570343428","https://openalex.org/W2945580137","https://openalex.org/W2951894856","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2964166085","https://openalex.org/W3008115128","https://openalex.org/W3018757597","https://openalex.org/W3042011474","https://openalex.org/W3091369929","https://openalex.org/W3140285855","https://openalex.org/W3164200338","https://openalex.org/W4205900964","https://openalex.org/W4210457271","https://openalex.org/W4220827132","https://openalex.org/W4224306993","https://openalex.org/W4309633513","https://openalex.org/W4310007323","https://openalex.org/W4360605034","https://openalex.org/W4386076325","https://openalex.org/W6604561885","https://openalex.org/W6631660994","https://openalex.org/W6638020065","https://openalex.org/W6640442106","https://openalex.org/W6750227808","https://openalex.org/W6760424586","https://openalex.org/W6782674554","https://openalex.org/W6796223860","https://openalex.org/W6798838024"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,24],"networks":[2,25],"(CNNs)":[3],"for":[4,47,79,212],"powerful":[5],"visual":[6,38],"image":[7,39,48],"analysis":[8,40],"are":[9,31,165],"gaining":[10],"popularity":[11],"in":[12,18,61,103,241],"artificial":[13,23],"intelligence.":[14],"The":[15,87],"main":[16,88],"difference":[17,127],"CNNs":[19,81],"compared":[20,171],"to":[21,55,91,138,172,188,237],"other":[22],"is":[26,53,90,111,121,131,161,231],"that":[27,58,206],"many":[28],"convolutional":[29,105,182],"layers":[30],"added,":[32],"which":[33],"improve":[34],"the":[35,43,97,101,108,119,124,135,157,173,178,181,184,197,201,221,250],"performance":[36,120],"of":[37,100,116,128,180,203],"by":[41,82,95,167,233],"extracting":[42],"feature":[44],"maps":[45],"required":[46,54],"classification.":[49],"However,":[50],"algorithm":[51,76,141],"optimization":[52,77],"run":[56],"applications":[57],"require":[59],"low-latency":[60],"edge":[62,209],"compute":[63,210,239],"modules":[64,211,240],"with":[65,113],"limited":[66],"processing":[67,205],"resources.":[68],"In":[69,200,225],"this":[70],"paper,":[71],"we":[72],"propose":[73],"a":[74,150,154,242],"novel":[75],"method":[78,110],"fast":[80,143],"using":[83,96,142,213],"continuous":[84,129],"differential":[85,98],"images.":[86],"idea":[89],"reduce":[92],"computation":[93],"variably":[94],"value":[99,126],"input":[102,158],"each":[104],"layer.":[106],"Also,":[107],"proposed":[109],"compatible":[112],"all":[114],"types":[115],"CNNs,":[117],"and":[118,145,220],"better":[122],"when":[123,156],"pixel":[125],"images":[130],"low.":[132],"We":[133],"use":[134],"DarkNet":[136],"framework":[137],"evaluate":[139],"our":[140],"convolution":[144,147,215],"half":[146,214],"approaches":[148],"on":[149],"clustered":[151,244],"system.":[152],"As":[153],"result,":[155],"frame":[159],"rate":[160],"10":[162],"fps,":[163],"FLOPs":[164,179,217],"reduced":[166,218],"about":[168,189],"4.92":[169],"times":[170,194],"original":[174,198],"YOLOv7-tiny.":[175,199],"By":[176],"reducing":[177],"layer,":[183],"inference":[185],"speed":[186,223],"increases":[187],"4.86":[190],"FPS,":[191],"performing":[192],"1.57":[193],"faster":[195,227],"than":[196],"case":[202],"parallel":[204],"used":[207],"two":[208],"approach,":[216],"more,":[219],"response":[222],"improved.":[224],"addition,":[226],"Object":[228],"detection":[229],"implementation":[230],"possible":[232],"additionally":[234],"expanding":[235],"up":[236],"7":[238],"scalable":[243],"embedded":[245],"system":[246],"as":[247,249],"much":[248],"user":[251],"wants.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
