{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T06:35:24Z","timestamp":1775889324114,"version":"3.50.1"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Sichuan Science and Technology Program","award":["2024NSFSC0480"],"award-info":[{"award-number":["2024NSFSC0480"]}]},{"name":"Sichuan Science and Technology Program","award":["2024NSFSC0662"],"award-info":[{"award-number":["2024NSFSC0662"]}]},{"name":"Natural Science Foundation for Distinguished Young Scholars of Sichuan","award":["2023NSFSC1970"],"award-info":[{"award-number":["2023NSFSC1970"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62471103"],"award-info":[{"award-number":["62471103"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Aerosp. Electron. Syst."],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1109\/taes.2025.3590701","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T17:47:43Z","timestamp":1752860863000},"page":"15690-15706","source":"Crossref","is-referenced-by-count":4,"title":["POAA: A Partial Occlusion Adversarial Attack Method Against DNN-Based SAR Target Recognition"],"prefix":"10.1109","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4805-9891","authenticated-orcid":false,"given":"Yanjing","family":"Ma","sequence":"first","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4616-6642","authenticated-orcid":false,"given":"Jifang","family":"Pei","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6136-0147","authenticated-orcid":false,"given":"Weibo","family":"Huo","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6761-2269","authenticated-orcid":false,"given":"Yin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3930-9323","authenticated-orcid":false,"given":"Yulin","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4726-8384","authenticated-orcid":false,"given":"Jianyu","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Synthetic Aperture Radar","volume":"11","author":"Curlander","year":"1991"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2013.2248301"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.1986.310772"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/7.937475"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1049\/iet-rsn.2014.0296"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2017.2649160"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(95)00050-X"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.013"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1201\/9781420049176"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.4249\/scholarpedia.5947"},{"key":"ref11","article-title":"Intriguing properties of neural networks","author":"Szegedy","year":"2013"},{"key":"ref12","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1201\/9781351251389-8"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref15","article-title":"Adversarial transformation networks: Learning to generate adversarial examples","author":"Baluja","year":"2017"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/694"},{"key":"ref19","article-title":"Robust physical-world attacks on machine learning models","author":"Evtimov","year":"2017"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412236"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3156392"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICET51757.2021.9450944"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2020.102632"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2020.3038683"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3051641"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2021.3058011"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2022.3179171"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS52108.2023.10281447"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2022.3184311"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3213305"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2022.3206261"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2024.3456750"},{"key":"ref33","first-page":"507","article-title":"Large-margin softmax loss for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Liu","year":"2016"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1023\/B:JMIV.0000011325.36760.1e"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.50.221"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1979.4310076"},{"key":"ref37","volume-title":"Morphological Investigations","author":"Allen","year":"1979"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1995.488968"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-016-2474-6"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1117\/12.321859"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312.4400"},{"key":"ref43","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"ref44","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017"},{"key":"ref45","article-title":"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5 MB model size","author":"Iandola","year":"2016"},{"key":"ref46","article-title":"Adversarial patch","author":"Brown","year":"2017"},{"key":"ref47","article-title":"ATRNet-STAR: A large dataset and benchmark towards remote sensing object recognition in the wild","author":"Liu","year":"2025"},{"key":"ref48","first-page":"274","article-title":"Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Athalye","year":"2018"},{"issue":"356","key":"ref49","first-page":"1","article-title":"On the impact of hard adversarial instances on overfitting in adversarial training","volume":"25","author":"Liu","year":"2024","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Aerospace and Electronic Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7\/11283081\/11086091.pdf?arnumber=11086091","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T06:41:16Z","timestamp":1765262476000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11086091\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":49,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/taes.2025.3590701","relation":{},"ISSN":["0018-9251","1557-9603","2371-9877"],"issn-type":[{"value":"0018-9251","type":"print"},{"value":"1557-9603","type":"electronic"},{"value":"2371-9877","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12]]}}}