CGN: Class Gradient Network for the construction of adversarial samples
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
CGN: Class Gradient Network for the construction of adversarial samples
Authors
Keywords
-
Journal
INFORMATION SCIENCES
Volume -, Issue -, Pages 119855
Publisher
Elsevier BV
Online
2023-11-07
DOI
10.1016/j.ins.2023.119855
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- EGA-Net: Edge feature enhancement and global information attention network for RGB-D salient object detection
- (2023) Longsheng Wei et al. INFORMATION SCIENCES
- Noise-related face image recognition based on double dictionary transform learning
- (2023) Mengmeng Liao et al. INFORMATION SCIENCES
- Sensitive region-aware black-box adversarial attacks
- (2023) Chenhao Lin et al. INFORMATION SCIENCES
- Improving the invisibility of adversarial examples with perceptually adaptive perturbation
- (2023) Yaoyuan Zhang et al. INFORMATION SCIENCES
- A survey on adversarial attacks in computer vision: Taxonomy, visualization and future directions
- (2022) Teng Long et al. COMPUTERS & SECURITY
- Compound adversarial examples in deep neural networks
- (2022) Yanchun Li et al. INFORMATION SCIENCES
- Query-efficient decision-based attack via sampling distribution reshaping
- (2022) Xuxiang Sun et al. PATTERN RECOGNITION
- Query efficient black-box adversarial attack on deep neural networks
- (2022) Yang Bai et al. PATTERN RECOGNITION
- Meta-learning-based adversarial training for deep 3D face recognition on point clouds
- (2022) Cuican Yu et al. PATTERN RECOGNITION
- Collaborative Learning with Unreliability Adaptation for Semi-Supervised Image Classification
- (2022) Xiaoyang Huo et al. PATTERN RECOGNITION
- A discriminatively deep fusion approach with improved conditional GAN (im-cGAN) for facial expression recognition
- (2022) Zhe Sun et al. PATTERN RECOGNITION
- Multi-Source Adversarial Sample Attack on Autonomous Vehicles
- (2021) Zuobin Xiong et al. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
- Deep neural networks-based relevant latent representation learning for hyperspectral image classification
- (2021) Akrem Sellami et al. PATTERN RECOGNITION
- Adversarial Attacks and Defenses in Deep Learning
- (2020) Kui Ren et al. Engineering
- Transfer Learning for SAR Image Classification Via Deep Joint Distribution Adaptation Networks
- (2020) Jie Geng et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability
- (2020) Xiaowei Huang et al. Computer Science Review
- Generative adversarial networks
- (2020) Ian Goodfellow et al. COMMUNICATIONS OF THE ACM
- Multi-Scale Metric Learning for Few-Shot Learning
- (2020) Wen Jiang et al. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
- Towards a physical-world adversarial patch for blinding object detection models
- (2020) Yajie Wang et al. INFORMATION SCIENCES
- Adversarial Examples: Attacks and Defenses for Deep Learning
- (2019) Xiaoyong Yuan et al. IEEE Transactions on Neural Networks and Learning Systems
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started