{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T00:31:36Z","timestamp":1759883496665,"version":"build-2065373602"},"reference-count":61,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62272388","62172284"],"award-info":[{"award-number":["62272388","62172284"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong Provincial Key Lab of Integrated Communication, Sensing and Computation for Ubiquitous Internet of Things","award":["2023B1212010007"],"award-info":[{"award-number":["2023B1212010007"]}]},{"name":"GRF grants from Research Grants Council of Hong Kong","award":["CityU 11205624","11202623"],"award-info":[{"award-number":["CityU 11205624","11202623"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1109\/tmc.2025.3586625","type":"journal-article","created":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T13:53:47Z","timestamp":1751896427000},"page":"12471-12486","source":"Crossref","is-referenced-by-count":0,"title":["Enabling Effective OOD Detection via Plug-and-Play Network for Mobile Visual Applications"],"prefix":"10.1109","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6759-1311","authenticated-orcid":false,"given":"Zixiao","family":"Wang","sequence":"first","affiliation":[{"name":"Northwest University, Xi’an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Dong","sequence":"additional","affiliation":[{"name":"Northwest University, Xi’an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7526-7269","authenticated-orcid":false,"given":"Tianzhang","family":"Xing","sequence":"additional","affiliation":[{"name":"Northwest University, Xi’an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0211-877X","authenticated-orcid":false,"given":"Zhidan","family":"Liu","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3296-3392","authenticated-orcid":false,"given":"Zhenjiang","family":"Li","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1180-6806","authenticated-orcid":false,"given":"Xiaojiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Northwest University, Xi’an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00036"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3594739.3610691"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3594739.3610711"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC48978.2021.9564545"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671785"},{"key":"ref6","first-page":"954","article-title":"Do deep generative models know what they don\u2019t know?","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Nalisnick"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01096"},{"key":"ref8","first-page":"2410","article-title":"A baseline for detecting misclassified and out-of-distribution examples in neural networks.","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Hendrycks"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5966"},{"key":"ref10","first-page":"8771","article-title":"Input complexity and out-of-distribution detection with likelihood-based generative models","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Serra"},{"key":"ref11","first-page":"20434","article-title":"SIREN: Shaping representations for detecting out-of-distribution objects","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Du"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01087"},{"key":"ref13","first-page":"16071","article-title":"Non-parametric outlier synthesis","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Tao"},{"key":"ref14","first-page":"6596","article-title":"VOS: Learning what you don\u2019t know by virtual outlier synthesis","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Du"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00596"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02142"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-024-02117-4"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_38"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i16.17690"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3570361.3592524"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00487"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS47876.2019.00077"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3116668"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref25","first-page":"21","article-title":"Energy-based out-of-distribution detection","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Liu"},{"key":"ref26","article-title":"A tutorial on energy-based learning","volume-title":"Predicting Structured Data","author":"LeCun","year":"2006"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01628"},{"key":"ref28","first-page":"3122","article-title":"Learning bounds for open-set learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Fang"},{"key":"ref29","first-page":"6810","article-title":"Benchmarking neural network robustness to common corruptions and perturbations","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Hendrycks"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00271"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01316-z"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"article-title":"Advanced auto labeling solution with added features","year":"2023","author":"Wang","key":"ref39"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2016.7759186"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/2968219.2971389"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/2820975.2820980"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3081333.3081336"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/2968219.2971461"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOM.2011.5935040"},{"author":"Howard","key":"ref46","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"ref49","first-page":"1088","article-title":"You only look once - object detection models: A review","volume-title":"Proc. Int. Conf. Comput. Sustain. Glob. Develop.","author":"Nazir"},{"key":"ref50","first-page":"113","article-title":"Rethinking the value of network pruning","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Liu"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-023-06379-w"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref53","first-page":"677","article-title":"On the importance of gradients for detecting distributional shifts in the wild","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Huang"},{"key":"ref54","first-page":"7174","article-title":"SSD: A unified framework for self-supervised outlier detection","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Sehwag"},{"key":"ref55","first-page":"11","article-title":"CSI: Novelty detection via contrastive learning on distributionally shifted instances","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tack"},{"key":"ref56","first-page":"212","article-title":"Robust subspace recovery layer for unsupervised anomaly detection","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Lai"},{"key":"ref57","first-page":"954","article-title":"Do deep generative models know what they don\u2019t know?","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Nalisnick"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01331"},{"key":"ref59","first-page":"15663","article-title":"Using self-supervised learning can improve model robustness and uncertainty","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Hendrycks"},{"key":"ref60","first-page":"2546","article-title":"Training confidence-calibrated classifiers for detecting out-of-distribution samples","volume-title":"Proc. Int. Conf. Learn. Representations.","author":"Lee"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20053-3_14"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7755\/11192678\/11072361.pdf?arnumber=11072361","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T17:54:28Z","timestamp":1759859668000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11072361\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":61,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2025.3586625","relation":{},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"type":"print","value":"1536-1233"},{"type":"electronic","value":"1558-0660"},{"type":"electronic","value":"2161-9875"}],"subject":[],"published":{"date-parts":[[2025,11]]}}}