{"id":"https://openalex.org/W7160596784","doi":"https://doi.org/10.1145/3774906.3802757","title":"ApproxBit: Efficient Video Analytics through Latency-Aware Offloading with Learned Binary Codes","display_name":"ApproxBit: Efficient Video Analytics through Latency-Aware Offloading with Learned Binary Codes","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160596784","doi":"https://doi.org/10.1145/3774906.3802757"},"language":null,"primary_location":{"id":"doi:10.1145/3774906.3802757","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774906.3802757","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774906.3802757","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051214410","display_name":"H Kim","orcid":null},"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":"Hyunseung Kim","raw_affiliation_strings":["Purdue University, West Lafayette, Indiana, USA"],"raw_orcid":"https://orcid.org/0009-0001-3303-5555","affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, Indiana, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004872134","display_name":"Sheetal Prasanna","orcid":null},"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":"Sheetal Prasanna","raw_affiliation_strings":["Purdue University, West Lafayette, Indiana, USA"],"raw_orcid":"https://orcid.org/0009-0002-5546-3697","affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, Indiana, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135716127","display_name":"Yin Li","orcid":"https://orcid.org/0000-0003-4173-9453"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yin Li","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, Wisconsin, USA"],"raw_orcid":"https://orcid.org/0000-0003-4173-9453","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055585728","display_name":"Somali Chaterji","orcid":"https://orcid.org/0000-0002-3651-6362"},"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":"Somali Chaterji","raw_affiliation_strings":["Purdue University, West Lafayette, Indiana, USA"],"raw_orcid":"https://orcid.org/0000-0002-3651-6362","affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, Indiana, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047310442","display_name":"Saurabh Bagchi","orcid":"https://orcid.org/0000-0002-4239-5632"},"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":"Saurabh Bagchi","raw_affiliation_strings":["Purdue University and KeyByte, West Lafayette, Indiana, USA"],"raw_orcid":"https://orcid.org/0000-0002-4239-5632","affiliations":[{"raw_affiliation_string":"Purdue University and KeyByte, West Lafayette, Indiana, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1179","last_page":"1193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.7240999937057495,"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"}},"topics":[{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.7240999937057495,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.06809999793767929,"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/T14347","display_name":"Big Data and Digital Economy","score":0.0215000007301569,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/analytics","display_name":"Analytics","score":0.6985999941825867},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5205000042915344},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.510200023651123},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4943000078201294},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.47429999709129333},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.44339999556541443},{"id":"https://openalex.org/keywords/scalable-video-coding","display_name":"Scalable Video Coding","score":0.43619999289512634},{"id":"https://openalex.org/keywords/uncompressed-video","display_name":"Uncompressed video","score":0.3962000012397766},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.3799999952316284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8500000238418579},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.6985999941825867},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5205000042915344},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.510200023651123},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4943000078201294},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.47429999709129333},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C133529210","wikidata":"https://www.wikidata.org/wiki/Q1076113","display_name":"Scalable Video Coding","level":3,"score":0.43619999289512634},{"id":"https://openalex.org/C162478608","wikidata":"https://www.wikidata.org/wiki/Q4011369","display_name":"Uncompressed video","level":4,"score":0.3962000012397766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38100001215934753},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.3799999952316284},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37959998846054077},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3790000081062317},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35280001163482666},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.30390000343322754},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C106030495","wikidata":"https://www.wikidata.org/wiki/Q1797012","display_name":"Video compression picture types","level":4,"score":0.29840001463890076},{"id":"https://openalex.org/C22561748","wikidata":"https://www.wikidata.org/wiki/Q854954","display_name":"Videoconferencing","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C151211776","wikidata":"https://www.wikidata.org/wiki/Q2778015","display_name":"Video capture","level":3,"score":0.2705000042915344},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2671999931335449},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C124828224","wikidata":"https://www.wikidata.org/wiki/Q2632668","display_name":"Macroblock","level":3,"score":0.2522999942302704},{"id":"https://openalex.org/C2988454689","wikidata":"https://www.wikidata.org/wiki/Q173131","display_name":"Digital video","level":3,"score":0.2522999942302704},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774906.3802757","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774906.3802757","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774906.3802757","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774906.3802757","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G690769368","display_name":"Collaborative Research: CPS: Frontier: CHORUS: Resilient Distributed CPS through Rational and Dynamic Decision-Making Among Multiple Stakeholders","funder_award_id":"2333487","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8624555679","display_name":null,"funder_award_id":"W911NF-2020-221","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W2024066070","https://openalex.org/W2062284132","https://openalex.org/W2101788345","https://openalex.org/W2129861682","https://openalex.org/W2346092678","https://openalex.org/W2546536770","https://openalex.org/W2563817822","https://openalex.org/W2625366777","https://openalex.org/W2626129225","https://openalex.org/W2799197246","https://openalex.org/W2860338957","https://openalex.org/W2911524385","https://openalex.org/W2920031528","https://openalex.org/W2962934715","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2963728985","https://openalex.org/W2963820951","https://openalex.org/W2980856918","https://openalex.org/W2981114133","https://openalex.org/W2981385151","https://openalex.org/W2981548405","https://openalex.org/W3003604113","https://openalex.org/W3035382196","https://openalex.org/W3046754651","https://openalex.org/W3049640275","https://openalex.org/W3109233295","https://openalex.org/W3144502021","https://openalex.org/W3156189202","https://openalex.org/W3173621652","https://openalex.org/W3183283270","https://openalex.org/W3188414697","https://openalex.org/W3214948528","https://openalex.org/W4206684810","https://openalex.org/W4236099117","https://openalex.org/W4244017338","https://openalex.org/W4283212161","https://openalex.org/W4285483958","https://openalex.org/W4304099300","https://openalex.org/W4312769131","https://openalex.org/W4328030459","https://openalex.org/W4386057769","https://openalex.org/W4386083026","https://openalex.org/W4386952192","https://openalex.org/W4387968598","https://openalex.org/W4389520460","https://openalex.org/W4399323055","https://openalex.org/W4402592632","https://openalex.org/W4402716218","https://openalex.org/W4402772372","https://openalex.org/W4404784276","https://openalex.org/W4405908054","https://openalex.org/W4413158162","https://openalex.org/W7133233472"],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,57,83,106,125,142,147,158,187],"growing":[2],"ubiquity":[3],"of":[4,209,227],"video":[5,8,25,44,90,103,113,117,126,174,189,234],"content,":[6],"efficient":[7,153],"analytics":[9,26,45,104,175],"has":[10,50],"become":[11],"essential":[12],"for":[13,41,102,173],"applications":[14],"such":[15],"as":[16],"surveillance,":[17],"autonomous":[18],"driving,":[19],"and":[20,32,116,135,138,152,197,199,205,211,239,252],"augmented":[21],"reality.":[22],"Yet,":[23],"deploying":[24],"models":[27],"on":[28,47,141,146,176,186],"resource-constrained":[29],"edge":[30,48,58,177],"devices":[31,49],"in":[33,254],"low-bandwidth":[34],"environments":[35],"remains":[36],"challenging.":[37],"A":[38],"dominant":[39],"method":[40],"handling":[42],"demanding":[43],"tasks":[46],"been":[51],"to":[52,60,67,82,97,132,165,248],"offload":[53,68,136],"computation":[54],"strategically":[55],"from":[56],"device":[59],"servers.":[61],"However,":[62],"all":[63],"prior":[64],"solutions":[65],"fail":[66],"under":[69],"severely":[70],"constrained,":[71],"real-world":[72,256],"network":[73,148,250],"conditions":[74],"(such":[75],"as,":[76],"a":[77,95,255],"few-Mbps":[78],"satellite":[79],"network)":[80],"due":[81],"much":[84],"higher":[85],"data":[86,154],"rates":[87],"associated":[88],"with":[89,111,180],"tasks.":[91],"We":[92,183,243],"introduce":[93],"ApproxBit,":[94],"system":[96],"optimize":[98],"shared":[99],"edge-to-cloud":[100],"processing":[101],"tasks;":[105],"two":[107,188],"that":[108],"we":[109],"experiment":[110],"are":[112,213],"action":[114],"recognition":[115],"question":[118],"answering.":[119],"ApproxBit":[120,185],"integrates":[121],"an":[122,170],"encoder":[123],"within":[124],"model,":[127],"uses":[128],"learned":[129],"binary":[130],"codes":[131],"effectively":[133],"compress":[134],"data,":[137],"adaptively":[139],"decides":[140],"offloading":[143,226],"point":[144],"depending":[145],"bandwidth.":[149],"ApproxBit\u2019s":[150,246],"adaptive":[151],"compression,":[155],"which":[156],"reduces":[157],"original":[159],"feature":[160],"map":[161],"size":[162],"by":[163],"up":[164],"2142.4":[166],"\u00d7,":[167],"makes":[168],"it":[169],"ideal":[171],"solution":[172],"devices,":[178],"especially":[179],"constrained":[181],"networks.":[182],"evaluate":[184],"tasks,":[190],"across":[191],"different":[192],"model":[193],"architectures":[194],"(e.g.,":[195,202],"convolution-":[196],"Transformer-based)":[198],"multiple":[200],"datasets":[201],"Something-Something-v2,":[203],"Kinetics,":[204],"MSVD).":[206],"Our":[207],"results":[208],"latency":[210],"accuracy":[212],"superior":[214],"over":[215],"baselines:":[216],"edge-only":[217],"processing,":[218,220],"server-only":[219],"DNN":[221],"Surgery":[222],"[ToCC":[223],"\u201923],":[224],"full":[225],"H.264-encoded":[228],"videos,":[229],"DeepCOD":[230],"[SenSys":[231],"\u201920],":[232],"neural":[233],"compression":[235],"DCVC-FM":[236],"[CVPR":[237],"\u201924],":[238],"LimitNet":[240],"[MobiSys":[241],"\u201924].":[242],"also":[244],"demonstrate":[245],"adaptivity":[247],"changing":[249],"conditions,":[251],"generalization":[253],"user":[257],"study.":[258]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-05-09T00:00:00"}
