{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T17:43:45Z","timestamp":1772041425252,"version":"3.50.1"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100017441","name":"United States Special Operations Command","doi-asserted-by":"publisher","award":["H92222-15-3-0001-01"],"award-info":[{"award-number":["H92222-15-3-0001-01"]}],"id":[{"id":"10.13039\/100017441","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1109\/tetci.2024.3485677","type":"journal-article","created":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T19:42:41Z","timestamp":1735760561000},"page":"961-971","source":"Crossref","is-referenced-by-count":3,"title":["ESAI: Efficient Split Artificial Intelligence via Early Exiting Using Neural Architecture Search"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3916-5841","authenticated-orcid":false,"given":"Behnam","family":"Zeinali","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, University of South Florida Tampa, Tampa, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4569-7123","authenticated-orcid":false,"given":"Di","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of South Florida Tampa, Tampa, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0660-7191","authenticated-orcid":false,"given":"J. Morris","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of South Florida Tampa, Tampa, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/DESEC.2017.8073832"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2881657"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2951419"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2590472"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.09.046"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.12.002"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/DESEC.2017.8073826"},{"key":"ref8","article-title":"Google cloud automl","year":"2018"},{"key":"ref9","first-page":"1","article-title":"Distilling the knowledge in a neural network","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hinton","year":"2015"},{"key":"ref10","first-page":"2654","article-title":"Do deep nets really need to be deep?","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ba","year":"2014"},{"key":"ref11","article-title":"Model compression via distillation and quantization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Polino","year":"2018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2018.00154"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3093337.3037698"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IPSN.2016.7460664"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2967734"},{"key":"ref16","first-page":"1","article-title":"Simple and efficient architecture search for convolutional neural networks","volume-title":"Proc. Int. Joint Conf. Artif. Intell.","author":"Elsken","year":"2017"},{"key":"ref17","article-title":"Skin lesion analysis toward melanoma detection: A challenge at the international symposium on biomedical imaging (ISBI) 2016, hosted by the international skin imaging collaboration (ISIC)","author":"Gutman","year":"2016"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363547"},{"issue":"12","key":"ref19","first-page":"2793","article-title":"Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (ISIC)","volume":"38","author":"Codella","year":"2019","journal-title":"IEEE Trans. Med. Imag."},{"key":"ref20","volume-title":"Active Learning: Theory and Applications","volume":"1","author":"Tong","year":"2001"},{"key":"ref21","article-title":"Squeezenet: Alexnet-level accuracy with 50x fewer parameters and < 0.5 mb model size","author":"Iandola","year":"2016"},{"key":"ref22","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Krizhevsky","year":"2012"},{"key":"ref23","article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref27","first-page":"6105","article-title":"Efficientnet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"Tan"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3081333.3081360"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3007787.3001163"},{"key":"ref30","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Han","year":"2016"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3210240.3210337"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2018.2858384"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.541"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3349614.3356022"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2016.7900006"},{"key":"ref36","first-page":"4310","article-title":"Multi-scale dense networks for resource efficient image classification","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Huang","year":"2017"},{"key":"ref37","first-page":"2740","article-title":"Doubly nested network for resource-efficient inference","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Kim","year":"2018"},{"key":"ref38","first-page":"2548","article-title":"Graph hypernetworks for neural architecture search","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Zhang","year":"2019"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00144"},{"key":"ref40","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Simonyan","year":"2015"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.5555\/3298023.3298188"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_2"},{"key":"ref48","article-title":"Darts: Differentiable architecture search","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Liu","year":"2019"},{"issue":"6","key":"ref49","first-page":"1","article-title":"Knowledge distillation: A survey","volume":"43","author":"Gou","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"issue":"11","key":"ref51","first-page":"4749","article-title":"A survey of model compression and acceleration for deep neural networks","volume":"31","author":"Cheng","year":"2020","journal-title":"IEEE Trans. Neural Networks Learn. Syst."},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/s11517-021-02355-5"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30367-9_11"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2018.161"},{"issue":"5","key":"ref56","first-page":"1212","article-title":"BCN20000: Dermoscopic lesions in the wild","volume":"82","author":"Combalia","year":"2020","journal-title":"J. Am. Acad. Dermatol."}],"container-title":["IEEE Transactions on Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7433297\/10850886\/10819965.pdf?arnumber=10819965","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T18:36:24Z","timestamp":1737743784000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10819965\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":56,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2024.3485677","relation":{},"ISSN":["2471-285X"],"issn-type":[{"value":"2471-285X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2]]}}}