Delving into Diversity in Substitute Ensembles and Transferability of Adversarial Examples. - Jie Hang; Keji Han; Yun Li 009 (ICONIP (3), 2018)

Adversarial Training Based Feature Selection. - Binghui Liu; Keji Han; Jie Hang; Yun Li 009 (SciSec, 2019)

Adversary resistant deep neural networks via advanced feature nullification. - Keji Han; Yun Li 009; Jie Hang (Knowl. Based Syst., 2019)

A Way to Explore the Lower Bound of Adversarial Perturbation. - Keji Han; Yuxuan Bai; Yun Li 009 (BigComp, 2020)

Is It Time to Redefine the Classification Task for Deep Neural Networks? - Keji Han; Yun Li 009 (CoRR, 2020)

Ensemble adversarial black-box attacks against deep learning systems. - Jie Hang; Keji Han; Hui Chen; Yun Li 009 (Pattern Recognit., 2020)

Transferable Interpolated Adversarial Attack with Random-Layer Mixup. - Size Ma; Keji Han; Xianzhong Long; Yun Li 009 (PAKDD (2), 2022)

(AD)2: Adversarial domain adaptation to defense with adversarial perturbation removal. - Keji Han; Bin Xia 003; Yun Li 009 (Pattern Recognit., 2022)

Advancing Example Exploitation Can Alleviate Critical Challenges in Adversarial Training. - Yao Ge 004; Yun Li 009; Keji Han; Junyi Zhu 006; Xianzhong Long (ICCV, 2023)

Attribution of Adversarial Attacks via Multi-task Learning. - Zhongyi Guo; Keji Han; Yao Ge 004; Yun Li 009; Wei Ji (ICONIP (2), 2023)

Scalable Attribution of Adversarial Attacks via Multi-Task Learning. - Zhongyi Guo; Keji Han; Yao Ge 004; Wei Ji; Yun Li 009 (CoRR, 2023)

Feature-aware transferable adversarial attacks against image classification. - Shuyan Cheng; Peng Li 011; Keji Han; He Xu (Appl. Soft Comput., 2024)

Rethinking the validity of perturbation in single-step adversarial training. - Yao Ge 004; Yun Li 009; Keji Han (Pattern Recognit., 2025)

DLR: Adversarial examples detection and label recovery for deep neural networks. - Keji Han; Yao Ge 004; Ruchuan Wang; Yun Li 009 (Pattern Recognit. Lett., 2025)

Probabilistic adaptive learning for enhanced speech emotion recognition in the presence of noisy labels. - Huijuan Zhao; Keji Han; Weibei Fan; Ning Ye; Ruchuan Wang 001 (Expert Syst. Appl., 2026)