SAR target recognition based on deep learning. - Sizhe Chen; Haipeng Wang 002 (DSAA, 2014)

Application of deep-learning algorithms to MSTAR data. - Haipeng Wang 002; Sizhe Chen; Feng Xu 001; Ya-Qiu Jin (IGARSS, 2015)

Target Classification Using the Deep Convolutional Networks for SAR Images. - Sizhe Chen; Haipeng Wang 002; Feng Xu 001; Ya-Qiu Jin (IEEE Trans. Geosci. Remote. Sens., 2016)

SAR Automatic Target Recognition Using a Roto-Translational Invariant Wavelet-Scattering Convolution Network. - Haipeng Wang 002; Suo Li; Yu Zhou; Sizhe Chen (Remote. Sens., 2018)

A Line Extraction Process Based on Noise Elimination and a Novel Benchmark in Jensen-Shannon Divergence. - Peidong Zhang; Sizhe Chen; Jingshi Yao (CIS/RAM, 2019)

DAmageNet: A Universal Adversarial Dataset. - Sizhe Chen; Xiaolin Huang; Zhengbao He; Chengjin Sun (CoRR, 2019)

Type I Attack For Generative Models. - Chengjin Sun; Sizhe Chen; Jia Cai; Xiaolin Huang (ICIP, 2020)

Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet. - Sizhe Chen; Zhengbao He; Chengjin Sun; Xiaolin Huang (CoRR, 2020)

Generate High-Resolution Adversarial Samples by Identifying Effective Features. - Sizhe Chen; Peidong Zhang; Chengjin Sun; Jia Cai; Xiaolin Huang (CoRR, 2020)

Double Backpropagation for Training Autoencoders against Adversarial Attack. - Chengjin Sun; Sizhe Chen; Xiaolin Huang (CoRR, 2020)

Attack on Multi-Node Attention for Object Detection. - Sizhe Chen; Fan He; Xiaolin Huang; Kun Zhang 001 (CoRR, 2020)

Colonoscopic Image Synthesis For Polyp Detector Enhancement Via Gan And Adversarial Training. - Fan He; Sizhe Chen; Shuaiyi Li; Lu Zhou; Haiqin Zhang; Haixia Peng; Xiaolin Huang (ISBI, 2021)

Improvement of AnyNet-based end-to-end phased binocular stereo matching network. - Sizhe Chen; Daji Ergu; Bo Ma; Ying Cai; Fangyao Liu (ITQM, 2021)

Going Far Boosts Attack Transferability, but Do Not Do It. - Sizhe Chen; Qinghua Tao; Zhixing Ye; Xiaolin Huang (CoRR, 2021)

QueryNet: An Efficient Attack Framework with Surrogates Carrying Multiple Identities. - Sizhe Chen; Zhehao Huang; Qinghua Tao; Xiaolin Huang (CoRR, 2021)

Dominant Patterns: Critical Features Hidden in Deep Neural Networks. - Zhixing Ye; Shaofei Qin; Sizhe Chen; Xiaolin Huang (CoRR, 2021)

Subspace Adversarial Training. - Tao Li 054; Yingwen Wu; Sizhe Chen; Kun Fang 004; Xiaolin Huang (CVPR, 2022)

Mutual Diverse-Label Adversarial Training. - Mingzhe Li; Sizhe Chen; Xiaolin Huang (ICONIP (1), 2022)

Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks. - Sizhe Chen; Zhehao Huang; Qinghua Tao; Yingwen Wu; Cihang Xie; Xiaolin Huang (NeurIPS, 2022)

Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet. - Sizhe Chen; Zhengbao He; Chengjin Sun; Jie Yang 002; Xiaolin Huang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Relevance attack on detectors. - Sizhe Chen; Fan He; Xiaolin Huang; Kun Zhang 001 (Pattern Recognit., 2022)

Soil Moisture Retrieval from the CyGNSS Data Based on a Bilinear Regression. - Sizhe Chen; Qingyun Yan; Shuanggen Jin; Weimin Huang 001; Tiexi Chen; Yan Jia 004; Shuci Liu; Qing Cao (Remote. Sens., 2022)

Investigating Catastrophic Overfitting in Fast Adversarial Training: A Self-fitting Perspective. - Zhengbao He; Tao Li; Sizhe Chen; Xiaolin Huang (CVPR Workshops, 2023)

Measuring the Transferability of ℓ∞ Attacks by the ℓ2 Norm. - Sizhe Chen; Qinghua Tao; Zhixing Ye; Xiaolin Huang (ICASSP, 2023)

Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors. - Sizhe Chen; Geng Yuan; Xinwen Cheng; Yifan Gong 004; Minghai Qin; Yanzhi Wang; Xiaolin Huang (ICLR, 2023)

One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks. - Shutong Wu; Sizhe Chen; Cihang Xie; Xiaolin Huang (ICLR, 2023)

Can LLMs Follow Simple Rules? - Norman Mu; Sarah Li Chen; Zifan Wang 001; Sizhe Chen; David Karamardian; Lulwa Aljeraisy; Dan Hendrycks; David A. Wagner 001 (CoRR, 2023)

Seasonal Effect of the Vegetation Clumping Index on Gross Primary Productivity Estimated by a Two-Leaf Light Use Efficiency Model. - Zhilong Li; Ziti Jiao; Chenxia Wang; Siyang Yin; Jing Guo 006; Yidong Tong; Ge Gao; Zheyou Tan; Sizhe Chen (Remote. Sens., 2023)

Unifying Gradients to Improve Real-World Robustness for Deep Networks. - Yingwen Wu; Sizhe Chen; Kun Fang 004; Xiaolin Huang (ACM Trans. Intell. Syst. Technol., 2023)

Jatmo: Prompt Injection Defense by Task-Specific Finetuning. - Julien Piet; Maha Alrashed; Chawin Sitawarin; Sizhe Chen; Zeming Wei; Elizabeth Sun; Basel Alomair; David A. Wagner 001 (ESORICS (1), 2024)

An Instance and Cloud Masks Guided Multi-source Fusion Network for Remote Sensing Object Detection. - Shouhong Wan; Sizhe Chen; Xiaoting Li; Peiquan Jin (PRICAI (3), 2024)

StruQ: Defending Against Prompt Injection with Structured Queries. - Sizhe Chen; Julien Piet; Chawin Sitawarin; David A. Wagner 001 (CoRR, 2024)

Aligning LLMs to Be Robust Against Prompt Injection. - Sizhe Chen; Arman Zharmagambetov; Saeed Mahloujifar; Kamalika Chaudhuri; Chuan Guo 001 (CoRR, 2024)

Query Attack by Multi-Identity Surrogates. - Sizhe Chen; Zhehao Huang; Qinghua Tao; Xiaolin Huang (IEEE Trans. Artif. Intell., 2024)

ClueCart: Supporting Game Story Interpretation and Narrative Inference from Fragmented Clues. - Xiyuan Wang; Yi-Fan Cao; Junjie Xiong; Sizhe Chen; Wenxuan Li; Junjie Zhang; Quan Li (CHI, 2025)

Prefer2SD: A Human-in-the-Loop Approach to Balancing Similarity and Diversity in In-Game Friend Recommendations. - Xiyuan Wang; Ziang Li; Sizhe Chen; Xingxing Xing; Wei Wan; Quan Li (IUI, 2025)

Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks. - Sizhe Chen; Arman Zharmagambetov; David A. Wagner 001; Chuan Guo 001 (CoRR, 2025)

Defending Against Prompt Injection With a Few DefensiveTokens. - Sizhe Chen; Yizhu Wang; Nicholas Carlini; Chawin Sitawarin; David A. Wagner 001 (CoRR, 2025)