{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T02:07:21Z","timestamp":1778983641703,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":27,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,2,9]],"date-time":"2023-02-09T00:00:00Z","timestamp":1675900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,2,9]]},"DOI":"10.1145\/3588155.3588183","type":"proceedings-article","created":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T18:57:19Z","timestamp":1686596239000},"page":"174-180","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["An Adversarial Attack Considering Effectiveness and Concealment on Faster R-CNN"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0362-7284","authenticated-orcid":false,"given":"Zhongjin","family":"Jiang","sequence":"first","affiliation":[{"name":"School of artificial intelligence, Jilin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5680-5664","authenticated-orcid":false,"given":"Jiawei","family":"Liu","sequence":"additional","affiliation":[{"name":"School of artificial intelligence, Jilin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6391-721X","authenticated-orcid":false,"given":"Xun","family":"Gong","sequence":"additional","affiliation":[{"name":"School of artificial intelligence, Jilin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3799-7994","authenticated-orcid":false,"given":"Yue","family":"Yin","sequence":"additional","affiliation":[{"name":"School of artificial intelligence, Jilin University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,6,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_2_1","first-page":"1","article-title":"Deep learning for detection of complete anterior cruciate ligament tear","year":"2019","unstructured":"Chang, P ., Tony T Wong and M. J. Rasiej. 2019. \u201cDeep learning for detection of complete anterior cruciate ligament tear,\u201d Journal of Digital Imaging, pp. 1\u20137.","journal-title":"Journal of Digital Imaging"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Wang D. Wei H. Zhang Z. Huang S. Xie J. Luo W. & Chen J. 2022. Non-Parametric Online Learning from Human Feedback for Neural Machine Translation.\u00a0AAAI.","DOI":"10.1609\/aaai.v36i10.21395"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1615\/JFlowVisImageProc.2021036124"},{"key":"e_1_3_2_1_5_1","volume-title":"Research on Small Target Pedestrian Detection Algorithm Based on Improved YOLOv3[C] \/\/International Conference on Genetic and Evolutionary Computing","author":"LIU S","unstructured":"LIU S, GENG Y, SONG Y, 2021. Research on Small Target Pedestrian Detection Algorithm Based on Improved YOLOv3[C] \/\/International Conference on Genetic and Evolutionary Computing. Springer, Singapore,:203-214."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2019.02.038"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"JENSEN M B NASROLLAHI K MOESLUND T B. 2017. Evaluating state-of-the-art object detector on challenging traffic light data[C]\/\/Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops 9-15.","DOI":"10.1109\/CVPRW.2017.122"},{"key":"e_1_3_2_1_8_1","first-page":"1","article-title":"Traffic light recognition using deep learning and prior maps for autonomous cars[C] \/\/2019 international joint conference on neural networks (IJCNN). Budapest, Hungary","author":"POSSATTI L C","year":"2019","unstructured":"POSSATTI L C, GUIDOLINI R, CARDOSO V B, 14-19 July 2019, Traffic light recognition using deep learning and prior maps for autonomous cars[C] \/\/2019 international joint conference on neural networks (IJCNN). Budapest, Hungary. IEEE, 1-8.","journal-title":"IEEE"},{"key":"e_1_3_2_1_9_1","volume-title":"Traffic signal image detection technology based on YOLO[C]\/\/Journal of Physics: Conference Series","author":"GAO H","year":"2012","unstructured":"GAO H, WANG W, YANG C, 2021. Traffic signal image detection technology based on YOLO[C]\/\/Journal of Physics: Conference Series. IOP Publishing, Guangzhou, China, 012012."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/a10040127"},{"key":"e_1_3_2_1_11_1","volume-title":"China.29-30","author":"YANG W","year":"2020","unstructured":"YANG W, ZHANG W. 2020. Real-time Traffic Signs Detection Based on YOLO Network Model[C] \/\/2020 International Conference on CyberEnabled Distributed Computing and Knowledge Discovery (CyberC). Chongqing, China.29-30 Oct. 2020 IEEE, 354-357."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3094201"},{"key":"e_1_3_2_1_13_1","unstructured":"Pei K Cao Y Yang J 2017. Towards practical verification of machine learning: The case of computer vision systems[J]. arXiv preprint arXiv:1712.01785."},{"key":"e_1_3_2_1_14_1","unstructured":"Szegedy Christian Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan I. Goodfellow and R. Fergus 2014. \u201cIntriguing properties of neural networks \u201d CoRR abs\/1312.6199."},{"key":"e_1_3_2_1_15_1","volume-title":"Jonathon Shlens and Christian Szegedy","author":"I.","year":"2015","unstructured":"Goodfellow, I., Jonathon Shlens and Christian Szegedy. 2015. \u201cExplaining and harnessing adversarial examples,\u201d CoRR abs\/1412.6572."},{"key":"e_1_3_2_1_16_1","volume-title":"Tsipras and Adrian Vladu","author":"D.","year":"2018","unstructured":"Madry, A., Aleksandar Makelov, Ludwig Schmidt, D. Tsipras and Adrian Vladu. 2018. \u201cTowards deep learning models resistant to adversarial attacks,\u201d ArXiv abs\/1706.06083."},{"key":"e_1_3_2_1_17_1","first-page":"39","volume-title":"IEEE Symposium on Security and Privacy (SP)","unstructured":"Carlini, Nicholas and David A. Wagner, 2017. \u201cTowards evaluating the robustness of neural networks,\u201d IEEE Symposium on Security and Privacy (SP), pp. 39-57."},{"key":"e_1_3_2_1_18_1","unstructured":"Zou Z Shi Z Guo Y 2019. Object Detection in 20 Years: A Survey[J]."},{"key":"e_1_3_2_1_19_1","unstructured":"Zeiler Matthew D. and Rob Fergus. 2013. \u201cStochastic Pooling for Regularization of Deep Convolutional Neural Networks.\u201d\u00a0CoRR\u00a0abs\/1301.3557 (2013): n. pag."},{"key":"e_1_3_2_1_20_1","first-page":"1378","article-title":"Adversarial Examples for Semantic Segmentation and Object Detection[J]","year":"2017","unstructured":"Xie C , Wang J , Zhang Z , 2017. Adversarial Examples for Semantic Segmentation and Object Detection[J]. IEEE Computer Society, 1378-1387.","journal-title":"IEEE Computer Society"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Wei X Liang S Chen N 2018. Transferable Adversarial Attacks for Image and Video Object Detection[C].","DOI":"10.24963\/ijcai.2019\/134"},{"key":"e_1_3_2_1_22_1","unstructured":"Li Y Tian D Mingching-Chang 2018. Robust Adversarial Perturbation on Deep Proposal-based Models[J]."},{"key":"e_1_3_2_1_23_1","volume-title":"Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples[J].","year":"2019","unstructured":"Wang D , Li C , Wen S , 2019. Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples[J]."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","unstructured":"J. Liu Y. Wang Y. Yin Y. Hu H. Chen and X. Gong 2021 \"Adversarial Attacks on Faster R-CNN: Design and Ablation Study \" 2021 China Automation Congress (CAC) pp. 7395-7400 doi: 10.1109\/CAC53003.2021.9728435.","DOI":"10.1109\/CAC53003.2021.9728435"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Ren S He K Girshick R 2016 Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[C]\/\/ NIPS.","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"e_1_3_2_1_26_1","volume-title":"COCO: Common objects in context","year":"2014","unstructured":"Lin, Tsung-Yi, M. Maire, Serge J. Belongie, James Hays, P . Perona, D.Ramanan, Piotr Doll\u00e1r and C. L. Zitnick, 2014, \u201cMicrosoft COCO: Common objects in context,\u201d ECCV"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","unstructured":"Z. Zhu D. Liang S. Zhang X. Huang B. Li and S. Hu 2016 \"Traffic-Sign Detection and Classification in the Wild \" 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 2110-2118 doi: 10.1109\/CVPR.2016.232.","DOI":"10.1109\/CVPR.2016.232"}],"event":{"name":"APIT 2023: 2023 5th Asia Pacific Information Technology Conference","location":"Ho Chi Minh City Vietnam","acronym":"APIT 2023"},"container-title":["Proceedings of the 2023 5th Asia Pacific Information Technology Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3588155.3588183","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3588155.3588183","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T01:43:12Z","timestamp":1778982192000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3588155.3588183"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,9]]},"references-count":27,"alternative-id":["10.1145\/3588155.3588183","10.1145\/3588155"],"URL":"https:\/\/doi.org\/10.1145\/3588155.3588183","relation":{},"subject":[],"published":{"date-parts":[[2023,2,9]]},"assertion":[{"value":"2023-06-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}