{"id":"https://openalex.org/W3173385564","doi":"https://doi.org/10.1109/aicas51828.2021.9458468","title":"Contention-aware Adaptive Model Selection for Machine Vision in Embedded Systems","display_name":"Contention-aware Adaptive Model Selection for Machine Vision in Embedded Systems","publication_year":2021,"publication_date":"2021-06-06","ids":{"openalex":"https://openalex.org/W3173385564","doi":"https://doi.org/10.1109/aicas51828.2021.9458468","mag":"3173385564"},"language":"en","primary_location":{"id":"doi:10.1109/aicas51828.2021.9458468","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas51828.2021.9458468","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)","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/A5087729884","display_name":"Ba\u015far K\u00fct\u00fck\u00e7\u00fc","orcid":"https://orcid.org/0000-0003-3868-421X"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Basar Kutukcu","raw_affiliation_strings":["University of California, San Diego"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017823328","display_name":"Sabur Baidya","orcid":"https://orcid.org/0000-0002-0245-2903"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sabur Baidya","raw_affiliation_strings":["University of California, San Diego"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065766721","display_name":"Anand Raghunathan","orcid":"https://orcid.org/0000-0002-4624-564X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anand Raghunathan","raw_affiliation_strings":["Electrical and Computer Engineering, Purdue University"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105369696","display_name":"Sujit Dey","orcid":"https://orcid.org/0000-0001-9671-3950"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sujit Dey","raw_affiliation_strings":["University of California, San Diego"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087729884"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":0.2005,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49613955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9988999962806702,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9988999962806702,"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":0.9987999796867371,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9871000051498413,"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":0.8350030779838562},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.745955228805542},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6353979110717773},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5530699491500854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5437681674957275},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4939728379249573},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.48905643820762634},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4867951571941376},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4408394694328308}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8350030779838562},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.745955228805542},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6353979110717773},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5530699491500854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5437681674957275},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4939728379249573},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.48905643820762634},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4867951571941376},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4408394694328308},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aicas51828.2021.9458468","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aicas51828.2021.9458468","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2133796295","https://openalex.org/W2279098554","https://openalex.org/W2319920447","https://openalex.org/W2560017826","https://openalex.org/W2797932837","https://openalex.org/W2953937638","https://openalex.org/W2955425717","https://openalex.org/W2962900737","https://openalex.org/W2963125010","https://openalex.org/W2963424132","https://openalex.org/W3026990304","https://openalex.org/W4243928383","https://openalex.org/W4252642235","https://openalex.org/W6695314431","https://openalex.org/W6700264148","https://openalex.org/W6730047919","https://openalex.org/W6762718338","https://openalex.org/W6764990469","https://openalex.org/W6777771897"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4312095940","https://openalex.org/W4210999218","https://openalex.org/W2963058055","https://openalex.org/W2511279186","https://openalex.org/W3112940371","https://openalex.org/W4283701126","https://openalex.org/W4224108623","https://openalex.org/W4317642197","https://openalex.org/W3157384330"],"abstract_inverted_index":{"Real-time":[0],"machine":[1,46],"vision":[2,47],"applications":[3,21,48],"running":[4],"on":[5,150],"resource-constrained":[6],"embedded":[7],"systems":[8],"face":[9],"challenges":[10],"for":[11,29,53,98,114],"maintaining":[12],"performance.":[13],"An":[14],"especially":[15],"challenging":[16],"scenario":[17],"arises":[18],"when":[19],"multiple":[20],"execute":[22],"at":[23],"the":[24,30,34,45,69,84,103,111,118,133,138,163],"same":[25],"time,":[26],"creating":[27],"contention":[28,37,73],"computational":[31],"resources":[32],"of":[33,44,71,93,106],"system.":[35],"This":[36],"results":[38],"in":[39,41,78,169],"increase":[40,77],"inference":[42,79,104,139],"delay":[43,80,140,170],"which":[49],"can":[50],"be":[51],"unacceptable":[52],"time-critical":[54],"tasks.":[55],"To":[56],"address":[57],"this":[58],"challenge,":[59],"we":[60],"propose":[61],"an":[62],"adaptive":[63],"model":[64,108,113,126,165],"selection":[65],"framework":[66,89,131,149],"to":[67,122],"mitigate":[68],"impact":[70],"system":[72,119],"and":[74,109,154],"prevent":[75],"unexpected":[76],"by":[81,135,166],"trading":[82],"off":[83],"application":[85],"accuracy":[86],"minimally.":[87],"The":[88],"uses":[90],"a":[91,123,143,160],"set":[92],"hierarchical":[94],"deep":[95],"learning":[96],"models":[97],"image":[99],"classification.":[100],"It":[101],"predicts":[102],"delays":[105],"each":[107,115],"selects":[110],"optimal":[112],"frame":[116],"considering":[117],"contention.":[120],"Compared":[121],"fixed":[124],"individual":[125,164],"with":[127],"similar":[128],"accuracy,":[129],"our":[130,148,157],"improves":[132],"performance":[134],"significantly":[136],"reducing":[137],"violations":[141],"against":[142],"practical":[144],"threshold.":[145],"We":[146],"implement":[147],"Nvidia":[151],"Jetson":[152],"TX2":[153],"show":[155],"that":[156],"approach":[158],"achieves":[159],"gain":[161],"over":[162],"27.6%":[167],"reductions":[168],"violations.":[171]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
