{"id":"https://openalex.org/W4205189174","doi":"https://doi.org/10.1109/avss52988.2021.9663806","title":"A Splittable DNN-Based Object Detector for Edge-Cloud Collaborative Real-Time Video Inference","display_name":"A Splittable DNN-Based Object Detector for Edge-Cloud Collaborative Real-Time Video Inference","publication_year":2021,"publication_date":"2021-11-16","ids":{"openalex":"https://openalex.org/W4205189174","doi":"https://doi.org/10.1109/avss52988.2021.9663806"},"language":"en","primary_location":{"id":"doi:10.1109/avss52988.2021.9663806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss52988.2021.9663806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-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/A5091809877","display_name":"Joo Chan Lee","orcid":"https://orcid.org/0000-0001-9398-9089"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Joo Chan Lee","raw_affiliation_strings":["Sungkyunkwan University, Suwon, South Korea"],"affiliations":[{"raw_affiliation_string":"Sungkyunkwan University, Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019873685","display_name":"Yongwoo Kim","orcid":"https://orcid.org/0000-0002-1011-2319"},"institutions":[{"id":"https://openalex.org/I157264075","display_name":"Sangmyung University","ror":"https://ror.org/01x4whx42","country_code":"KR","type":"education","lineage":["https://openalex.org/I157264075"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongwoo Kim","raw_affiliation_strings":["Sangmyung University, Cheonan, South Korea"],"affiliations":[{"raw_affiliation_string":"Sangmyung University, Cheonan, South Korea","institution_ids":["https://openalex.org/I157264075"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014287181","display_name":"SungTae Moon","orcid":"https://orcid.org/0000-0002-1638-6898"},"institutions":[{"id":"https://openalex.org/I2800747041","display_name":"Korea Aerospace Research Institute","ror":"https://ror.org/037pqnq23","country_code":"KR","type":"funder","lineage":["https://openalex.org/I2800747041","https://openalex.org/I2801339556","https://openalex.org/I4387152098","https://openalex.org/I4412460384"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"SungTae Moon","raw_affiliation_strings":["Korea Aerospace Research Institute, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"Korea Aerospace Research Institute, Daejeon, South Korea","institution_ids":["https://openalex.org/I2800747041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063908850","display_name":"Jong Hwan Ko","orcid":"https://orcid.org/0000-0003-4434-4318"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong Hwan Ko","raw_affiliation_strings":["Sungkyunkwan University, Suwon, South Korea"],"affiliations":[{"raw_affiliation_string":"Sungkyunkwan University, Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091809877"],"corresponding_institution_ids":["https://openalex.org/I848706"],"apc_list":null,"apc_paid":null,"fwci":1.2489,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.82263072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7799752354621887},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7260566353797913},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6699661016464233},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.5695697665214539},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5251992344856262},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5140160322189331},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5096545219421387},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4867813289165497},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4857681095600128},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4798850119113922},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4663618803024292},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4114688038825989},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.368166983127594},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3435634672641754},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3131093680858612},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.08002707362174988}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7799752354621887},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7260566353797913},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6699661016464233},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.5695697665214539},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5251992344856262},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5140160322189331},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5096545219421387},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4867813289165497},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4857681095600128},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4798850119113922},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4663618803024292},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4114688038825989},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.368166983127594},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3435634672641754},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3131093680858612},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.08002707362174988},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss52988.2021.9663806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss52988.2021.9663806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2193145675","https://openalex.org/W2570343428","https://openalex.org/W2918274546","https://openalex.org/W2925287836","https://openalex.org/W2962777203","https://openalex.org/W2962790536","https://openalex.org/W2963770864","https://openalex.org/W2964223234","https://openalex.org/W2971714613","https://openalex.org/W2989676862","https://openalex.org/W3015540635","https://openalex.org/W3018757597","https://openalex.org/W3034755948","https://openalex.org/W3034971973","https://openalex.org/W3043914740","https://openalex.org/W3044024778","https://openalex.org/W3047573586","https://openalex.org/W3106250896","https://openalex.org/W3107847925","https://openalex.org/W3133275180","https://openalex.org/W3158077430","https://openalex.org/W3160403640","https://openalex.org/W4236099117","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6750227808","https://openalex.org/W6750245737","https://openalex.org/W6763676353","https://openalex.org/W6777046832","https://openalex.org/W6794684839"],"related_works":["https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W4313463218","https://openalex.org/W4312996489","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W3106131444","https://openalex.org/W3216099748","https://openalex.org/W4205963435","https://openalex.org/W4319161913"],"abstract_inverted_index":{"While":[0],"recent":[1,41],"advances":[2],"in":[3,178],"deep":[4],"neural":[5],"networks":[6],"(DNNs)":[7],"enabled":[8],"remarkable":[9],"performance":[10,150],"on":[11,129,172],"various":[12],"computer":[13],"vision":[14],"tasks,":[15],"it":[16],"is":[17,75],"challenging":[18],"for":[19,57,65,117],"edge":[20,52,142],"devices":[21],"to":[22,31],"perform":[23],"real-time":[24,100],"inference":[25,39,143],"of":[26,79],"complex":[27],"DNN":[28,49],"models":[29],"due":[30],"their":[32],"stringent":[33],"resource":[34],"constraint.":[35],"To":[36,85],"enhance":[37],"the":[38,124,130,137,156,173],"throughput,":[40],"studies":[42],"proposed":[43,104,157],"collaborative":[44,99],"intelligence":[45],"(CI)":[46],"that":[47,96,111,155],"splits":[48],"computation":[50],"into":[51],"and":[53,133,141,163,168],"cloud":[54],"platforms,":[55],"mostly":[56],"simple":[58],"tasks":[59],"such":[60],"as":[61],"image":[62],"classification.":[63],"However,":[64],"general":[66],"DNN-based":[67],"object":[68,94],"detectors":[69],"with":[70],"a":[71,80,92,107,120],"branching":[72],"architecture,":[73],"CI":[74],"highly":[76],"restricted":[77],"because":[78],"significant":[81],"feature":[82,108,122,131,139],"transmission":[83],"overhead.":[84],"solve":[86],"this":[87,89],"issue,":[88],"paper":[90],"proposes":[91],"splittable":[93],"detector":[95],"enables":[97],"edge-cloud":[98],"video":[101],"inference.":[102],"The":[103,149],"architecture":[105],"includes":[106],"reconstruction":[109],"network":[110],"can":[112],"generate":[113],"multiple":[114],"features":[115],"required":[116],"detection":[118,147],"using":[119,152],"small-sized":[121],"from":[123],"edge-side":[125],"extractor.":[126],"Asymmetric":[127],"scaling":[128],"extractor":[132],"reconstructor":[134],"further":[135],"reduces":[136],"transmitted":[138],"size":[140],"latency,":[144],"while":[145],"maintaining":[146],"accuracy.":[148],"evaluation":[151],"Yolov5":[153],"shows":[154],"model":[158],"achieves":[159],"28":[160],"fps":[161],"(2.45X":[162],"1.56X":[164],"higher":[165],"than":[166],"edge-only":[167],"cloud-only":[169],"inference,":[170],"respectively),":[171],"NVIDIA":[174],"Jetson":[175],"TX2":[176],"platform":[177],"WiFi":[179],"environment.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5}],"updated_date":"2026-01-17T23:10:49.606395","created_date":"2025-10-10T00:00:00"}