{"id":"https://openalex.org/W7117125076","doi":"https://doi.org/10.1109/access.2025.3648049","title":"Confidence-Guided Multi-Exit Models for Energy-Optimized Object Detection in Road Environments","display_name":"Confidence-Guided Multi-Exit Models for Energy-Optimized Object Detection in Road Environments","publication_year":2025,"publication_date":"2025-12-24","ids":{"openalex":"https://openalex.org/W7117125076","doi":"https://doi.org/10.1109/access.2025.3648049"},"language":null,"primary_location":{"id":"doi:10.1109/access.2025.3648049","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3648049","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3648049","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061791436","display_name":"Cyreneo Dofitas","orcid":"https://orcid.org/0009-0003-3523-0770"},"institutions":[{"id":"https://openalex.org/I83202590","display_name":"Jeju National University","ror":"https://ror.org/05hnb4n85","country_code":"KR","type":"education","lineage":["https://openalex.org/I83202590"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Cyreneo Dofitas","raw_affiliation_strings":["Department of Electronic Engineering, Institute of Information Science and Technology, Jeju National University, Jeju-si, South Korea"],"raw_orcid":"https://orcid.org/0009-0003-3523-0770","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Institute of Information Science and Technology, Jeju National University, Jeju-si, South Korea","institution_ids":["https://openalex.org/I83202590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121127047","display_name":"Yong-Woon Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I83202590","display_name":"Jeju National University","ror":"https://ror.org/05hnb4n85","country_code":"KR","type":"education","lineage":["https://openalex.org/I83202590"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong-Woon Kim","raw_affiliation_strings":["Department of Computer Engineering, Jeju National University, Jeju-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4759-0138","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Jeju National University, Jeju-si, South Korea","institution_ids":["https://openalex.org/I83202590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121140674","display_name":"Yung-Cheol Byun","orcid":null},"institutions":[{"id":"https://openalex.org/I83202590","display_name":"Jeju National University","ror":"https://ror.org/05hnb4n85","country_code":"KR","type":"education","lineage":["https://openalex.org/I83202590"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yung-Cheol Byun","raw_affiliation_strings":["Department of Computer Engineering, Jeju National University, Jeju-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-1107-9941","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Jeju National University, Jeju-si, South Korea","institution_ids":["https://openalex.org/I83202590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I83202590"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.52171244,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"8718","last_page":"8736"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.982699990272522,"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":0.982699990272522,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.0017999999690800905,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.0012000000569969416,"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/object-detection","display_name":"Object detection","score":0.7692000269889832},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.7069000005722046},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.654699981212616},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.6273999810218811},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.6233000159263611},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5184999704360962},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.5131999850273132},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5113000273704529}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7997999787330627},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7692000269889832},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.7069000005722046},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.654699981212616},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.6273999810218811},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.6233000159263611},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5184999704360962},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.5131999850273132},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5113000273704529},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43130001425743103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4027999937534332},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39259999990463257},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3578999936580658},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3260999917984009},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2025.3648049","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3648049","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3648049","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3648049","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.7275199294090271}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2963037989","https://openalex.org/W2963163009","https://openalex.org/W3035564946","https://openalex.org/W3130618527","https://openalex.org/W3150672085","https://openalex.org/W3160220816","https://openalex.org/W3174620891","https://openalex.org/W3177399480","https://openalex.org/W3194319283","https://openalex.org/W3198451434","https://openalex.org/W3213199079","https://openalex.org/W3216668858","https://openalex.org/W4206599199","https://openalex.org/W4281707531","https://openalex.org/W4312632920","https://openalex.org/W4313889764","https://openalex.org/W4322503836","https://openalex.org/W4366394227","https://openalex.org/W4380925920","https://openalex.org/W4381327859","https://openalex.org/W4385521685","https://openalex.org/W4386394445","https://openalex.org/W4386412380","https://openalex.org/W4390777420","https://openalex.org/W4390874772","https://openalex.org/W4394625743","https://openalex.org/W4394744629","https://openalex.org/W4396827362","https://openalex.org/W4396988537","https://openalex.org/W4403192456","https://openalex.org/W4404835166","https://openalex.org/W4404944348","https://openalex.org/W4406002705","https://openalex.org/W4406486269","https://openalex.org/W4407168518","https://openalex.org/W4408327712","https://openalex.org/W4408594471","https://openalex.org/W4410215153","https://openalex.org/W4410393339","https://openalex.org/W4410398265","https://openalex.org/W4410748107","https://openalex.org/W4411331327","https://openalex.org/W4411344078","https://openalex.org/W4411949372","https://openalex.org/W4412605231","https://openalex.org/W4413124362","https://openalex.org/W4413146505","https://openalex.org/W4413359911"],"related_works":[],"abstract_inverted_index":{"Object":[0],"detection":[1],"is":[2,14],"central":[3],"to":[4,75,124,144,153],"autonomous":[5],"driving,":[6],"but":[7],"deploying":[8],"detectors":[9],"on":[10,101],"embedded":[11],"automotive":[12],"platforms":[13],"constrained":[15],"by":[16,119],"tight":[17],"power":[18],"and":[19,34,56,63,67,92,158],"latency":[20],"budgets.":[21],"Conventional":[22],"single-exit":[23,126,143],"networks":[24],"process":[25],"all":[26],"inputs":[27],"at":[28,181],"full":[29],"depth,":[30],"incurring":[31],"unnecessary":[32],"FLOPs":[33],"energy":[35,118,136],"even":[36],"for":[37,47,79],"easy":[38],"scenes.":[39],"This":[40],"paper":[41],"proposes":[42],"a":[43,64,70,125,129,155],"confidence-guided":[44,170],"multi-exit":[45,109],"framework":[46],"energy-optimized":[48],"road-scene":[49],"object":[50],"detection.":[51],"We":[52,82],"augment":[53],"the":[54,77,95,102,106,132,148,169],"MobileNet-V1/V2/V3":[55],"EfficientDet-D0":[57],"backbones":[58],"with":[59,142,163],"two":[60],"early":[61,87],"exits":[62],"final":[65],"head,":[66],"we":[68,93],"use":[69],"simple":[71],"softmax-based":[72],"confidence":[73],"rule":[74],"select":[76],"exit":[78],"each":[80],"input.":[81],"derive":[83],"conditions":[84],"under":[85,97,147],"which":[86],"exiting":[88],"reduces":[89],"expected":[90],"computation":[91],"bound":[94],"error":[96],"calibrated":[98],"confidence.":[99],"Experiments":[100],"dataset":[103],"show":[104],"that":[105],"proposed":[107],"MobileNet-V2":[108],"detector":[110],"achieves":[111],"92.3%":[112],"mAP@0.5":[113],"while":[114],"reducing":[115],"measured":[116],"GPU":[117],"14.73%":[120],"per":[121,137],"image":[122,138],"compared":[123],"baseline.":[127],"On":[128],"low-power":[130],"device,":[131],"same":[133],"model":[134],"lowers":[135],"from":[139],"2.67":[140],"J":[141,146],"2.26":[145],"dynamic":[149],"early-exit":[150],"policy,":[151],"corresponding":[152],"about":[154],"17%":[156],"reduction,":[157],"still":[159],"meets":[160],"real-time":[161],"constraints":[162],"72.5":[164],"ms":[165],"latency.":[166],"Across":[167],"backbones,":[168],"policy":[171],"consistently":[172],"yields":[173],"better":[174],"latency\u2013energy":[175],"trade-offs":[176],"than":[177],"prior":[178],"early\u2013exit":[179],"baselines":[180],"comparable":[182],"accuracy.":[183]},"counts_by_year":[],"updated_date":"2026-01-24T23:23:39.755997","created_date":"2025-12-24T00:00:00"}
