{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:16:21Z","timestamp":1770768981017,"version":"3.50.0"},"reference-count":18,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/1000000010","name":"NSF","doi-asserted-by":"publisher","award":["1910667,1910891,2025284"],"award-info":[{"award-number":["1910667,1910891,2025284"]}],"id":[{"id":"10.13039\/1000000010","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,28]]},"DOI":"10.1109\/icc45041.2023.10279417","type":"proceedings-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T13:54:10Z","timestamp":1698069250000},"page":"954-959","source":"Crossref","is-referenced-by-count":3,"title":["EPAM: A Predictive Energy Model for Mobile AI"],"prefix":"10.1109","author":[{"given":"Anik","family":"Mallik","sequence":"first","affiliation":[{"name":"The University of North Carolina,Department of Electrical and Computer Engineering,Charlotte,NC,USA"}]},{"given":"Haoxin","family":"Wang","sequence":"additional","affiliation":[{"name":"Georgia State University,Department of Computer Science,GA,USA"}]},{"given":"Jiang","family":"Xie","sequence":"additional","affiliation":[{"name":"The University of North Carolina,Department of Electrical and Computer Engineering,Charlotte,NC,USA"}]},{"given":"Dawei","family":"Chen","sequence":"additional","affiliation":[{"name":"Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,USA"}]},{"given":"Kyungtae","family":"Han","sequence":"additional","affiliation":[{"name":"Toyota Motor North America R&#x0026;D,InfoTech Labs,Mountain View,CA,USA"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3447993.3483269"},{"key":"ref12","article-title":"Where is the energy spent inside my app? Fine grained energy accounting on smartphones with eprof","author":"pathak","year":"0","journal-title":"Proc of ACM European Conference on Computer Systems"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.sustainlp-1.19"},{"key":"ref14","article-title":"LEAF+AIO: Edge-assisted energyaware object detection for mobile augmented reality","author":"wang","year":"2022","journal-title":"IEEE Trans on Mobile Computing"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/MM.2018.053631145"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS47876.2019.00077"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2935643.2935650"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.521"},{"key":"ref17","article-title":"An intuitive tutorial to Gaussian processes regression","author":"wang","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ITNT55410.2022.9848659"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065704001899"},{"key":"ref8","article-title":"Quantized CNN: A unified approach to accelerate and compress convolutional networks","author":"cheng","year":"2017","journal-title":"IEEE Trans on Neural Networks and Learning Systems"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00447"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.sustainlp-1.17"},{"key":"ref4","article-title":"Comparison and benchmarking of AI models and frameworks on mobile devices","author":"luo","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3409390.3409393"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICC45855.2022.9838862"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TGCN.2020.3041666"}],"event":{"name":"ICC 2023 - IEEE International Conference on Communications","location":"Rome, Italy","start":{"date-parts":[[2023,5,28]]},"end":{"date-parts":[[2023,6,1]]}},"container-title":["ICC 2023 - IEEE International Conference on Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10278505\/10278554\/10279417.pdf?arnumber=10279417","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T20:57:13Z","timestamp":1770757033000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10279417\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,28]]},"references-count":18,"URL":"https:\/\/doi.org\/10.1109\/icc45041.2023.10279417","relation":{},"subject":[],"published":{"date-parts":[[2023,5,28]]}}}