中国科学院计算技术研究所机构知识库

浏览/检索结果: 共8条，第1-8条

帮助

已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序期刊影响因子升序期刊影响因子降序题名升序题名降序WOS被引频次升序WOS被引频次降序
	AUCPro: AUC-Oriented Provable Robustness Learning 期刊论文 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2025, 卷号: 47, 期号: 6, 页码: 4579-4596 作者:  Bao, Shilong;  Xu, Qianqian;  Yang, Zhiyong;  He, Yuan;  Cao, Xiaochun;  Huang, Qingming 收藏  |  浏览/下载：2/0  |  提交时间：2025/12/03 Robustness  Training  Perturbation methods  Machine learning  Heavily-tailed distribution  Smoothing methods  Gaussian noise  Data mining  Standards  Protocols  AUC-oriented learning  adversarial robustness  machine learning
	Enhancing the Robustness of Vision-Language Foundation Models by Alignment Perturbation 期刊论文 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2025, 卷号: 20, 页码: 7091-7105 作者:  Zhang, Cong;  Wang, Shuhui;  Li, Xiaodan;  Zhu, Yao;  Qi, Honggang;  Huang, Qingming 收藏  |  浏览/下载：1/0  |  提交时间：2025/12/03 Multimedia forensics  adversarial perturbation  robust training  robust training  vision-language models  vision-language models  vision-language models
	Adaptive Perturbation for Adversarial Attack 期刊论文 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2024, 卷号: 46, 期号: 8, 页码: 5663-5676 作者:  Yuan, Zheng;  Zhang, Jie;  Jiang, Zhaoyan;  Li, Liangliang;  Shan, Shiguang 收藏  |  浏览/下载：31/0  |  提交时间：2024/12/06 Perturbation methods  Iterative methods  Adaptation models  Generators  Closed box  Security  Training  Adversarial attack  transfer-based attack  adversarial example  adaptive perturbation
	GCSA: A New Adversarial Example-Generating Scheme Toward Black-Box Adversarial Attacks 期刊论文 IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2024, 卷号: 70, 期号: 1, 页码: 2038-2048 作者:  Fan, Xinxin;  Li, Mengfan;  Zhou, Jia;  Jing, Quanliang;  Lin, Chi;  Lu, Yunfeng;  Bi, Jingping 收藏  |  浏览/下载：32/0  |  提交时间：2024/12/06 Closed box  Perturbation methods  Predictive models  Indexes  Training  Glass box  Optimization  Deep learning  adversarial examples  black-box adversarial attack  transferability
	Revisiting AUC-Oriented Adversarial Training With Loss-Agnostic Perturbations 期刊论文 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 12, 页码: 15494-15511 作者:  Yang, Zhiyong;  Xu, Qianqian;  Hou, Wenzheng;  Bao, Shilong;  He, Yuan;  Cao, Xiaochun;  Huang, Qingming 收藏  |  浏览/下载：43/0  |  提交时间：2024/05/20 Optimization  Training  Perturbation methods  Machine learning  Receivers  Machine learning algorithms  Linear programming  AUC Optimization  adversarial learning  machine learning
	Toward Understanding and Boosting Adversarial Transferability From a Distribution Perspective 期刊论文 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6487-6501 作者:  Zhu, Yao;  Chen, Yuefeng;  Li, Xiaodan;  Chen, Kejiang;  He, Yuan;  Tian, Xiang;  Zheng, Bolun;  Chen, Yaowu;  Huang, Qingming 收藏  |  浏览/下载：45/0  |  提交时间：2023/07/12 Data models  Perturbation methods  Iterative methods  Training  Distributed databases  Predictive models  Neural networks  Adversarial transferability  adversarial attack  black-box attack
	Exploring Adversarial Attack in Spiking Neural Networks With Spike-Compatible Gradient 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Liang, Ling;  Hu, Xing;  Deng, Lei;  Wu, Yujie;  Li, Guoqi;  Ding, Yufei;  Li, Peng;  Xie, Yuan 收藏  |  浏览/下载：59/0  |  提交时间：2022/06/21 Spatiotemporal phenomena  Computational modeling  Perturbation methods  Biological neural networks  Backpropagation  Unsupervised learning  Training  Adversarial attack  backpropagation through time (BPTT)  neuromorphic computing  spike-compatible gradient  spiking neural networks (SNNs)
	FCDM: A Methodology Based on Sensor Pattern Noise Fingerprinting for Fast Confidence Detection to Adversarial Attacks 期刊论文 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2020, 卷号: 39, 期号: 12, 页码: 4791-4804 作者:  Lan, Yazhu;  Nixon, Kent W.;  Guo, Qingli;  Zhang, Guohe;  Xu, Yuanchao;  Li, Hai;  Chen, Yiran 收藏  |  浏览/下载：96/0  |  提交时间：2021/12/01 Perturbation methods  Computational modeling  Data integrity  Detectors  Optimization  Field programmable gate arrays  Hardware  Adversarial attacks  confidence detection  deep neural networks (DNNs)  FPGA-based hardware architecture  sensor pattern noise (SPN)