{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:23:33Z","timestamp":1760149413006,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T00:00:00Z","timestamp":1691712000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61906213"],"award-info":[{"award-number":["61906213"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Object detection in remote sensing has developed rapidly and has been applied in many fields, but it is known to be vulnerable to adversarial attacks. Improving the robustness of models has become a key issue for reliable application deployment. This paper proposes a robust object detector for remote sensing images (RSIs) to mitigate the performance degradation caused by adversarial attacks. For remote sensing objects, multi-dimensional convolution is utilized to extract both specific features and consistency features from clean images and adversarial images dynamically and efficiently. This enhances the feature extraction ability and thus enriches the context information used for detection. Furthermore, regularization loss is proposed from the perspective of image distribution. This can separate consistent features from the mixed distributions for reconstruction to assure detection accuracy. Experimental results obtained using different datasets (HRSC, UCAS-AOD, and DIOR) demonstrate that the proposed method effectively improves the robustness of detectors against adversarial attacks.<\/jats:p>","DOI":"10.3390\/rs15163997","type":"journal-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T10:33:23Z","timestamp":1691750003000},"page":"3997","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Learning Adversarially Robust Object Detector with Consistency Regularization in Remote Sensing Images"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1837-541X","authenticated-orcid":false,"given":"Yang","family":"Li","sequence":"first","affiliation":[{"name":"Department of Space Information, Space Engineering University, Beijing 101416, China"},{"name":"Beijing Institute of Remote Sensing Information, Beijing 100192, China"},{"name":"Graduate School, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuqiang","family":"Fang","sequence":"additional","affiliation":[{"name":"Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanyun","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Space Information, Space Engineering University, Beijing 101416, China"},{"name":"Graduate School, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bitao","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Space Information, Space Engineering University, Beijing 101416, China"},{"name":"Beijing Institute of Remote Sensing Information, Beijing 100192, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengjin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi","family":"Li","sequence":"additional","affiliation":[{"name":"Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Li, Z., Wang, Y., Zhang, N., Zhang, Y., Zhao, Z., Xu, D., Ben, G., and Gao, Y. 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