Investigating and unmasking feature-level vulnerabilities of CNNs to adversarial perturbations
Fuente:
arXiv
Saved in:
| Main Authors: | Coppola, Davide, Lee, Hwee Kuan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards properties of adversarial image perturbations
by: Kuznetsov, Egor, et al.
Published: (2025)
by: Kuznetsov, Egor, et al.
Published: (2025)
Deep learning models are vulnerable, but adversarial examples are even more vulnerable
by: Li, Jun, et al.
Published: (2025)
by: Li, Jun, et al.
Published: (2025)
A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs
by: Stalder, Nicolas, et al.
Published: (2026)
by: Stalder, Nicolas, et al.
Published: (2026)
Investigating Market Strength Prediction with CNNs on Candlestick Chart Images
by: Duong, Thanh Nam, et al.
Published: (2025)
by: Duong, Thanh Nam, et al.
Published: (2025)
D-LORD for Motion Stylization
by: Gupta, Meenakshi, et al.
Published: (2024)
by: Gupta, Meenakshi, et al.
Published: (2024)
Designing Extremely Memory-Efficient CNNs for On-device Vision Tasks
by: Lee, Jaewook, et al.
Published: (2024)
by: Lee, Jaewook, et al.
Published: (2024)
Partial Large Kernel CNNs for Efficient Super-Resolution
by: Lee, Dongheon, et al.
Published: (2024)
by: Lee, Dongheon, et al.
Published: (2024)
OA-CNNs: Omni-Adaptive Sparse CNNs for 3D Semantic Segmentation
by: Peng, Bohao, et al.
Published: (2024)
by: Peng, Bohao, et al.
Published: (2024)
Reliable or Deceptive? Investigating Gated Features for Smooth Visual Explanations in CNNs
by: Mitra, Soham, et al.
Published: (2024)
by: Mitra, Soham, et al.
Published: (2024)
An adversarial feature learning based semantic communication method for Human 3D Reconstruction
by: Liu, Shaojiang, et al.
Published: (2024)
by: Liu, Shaojiang, et al.
Published: (2024)
Lightweight Channel Attention for Efficient CNNs
by: Kanaparthi, Prem Babu, et al.
Published: (2026)
by: Kanaparthi, Prem Babu, et al.
Published: (2026)
GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model
by: Zhu, Zhiyu, et al.
Published: (2024)
by: Zhu, Zhiyu, et al.
Published: (2024)
CNNs for Style Transfer of Digital to Film Photography
by: Mackenzie, Pierre, et al.
Published: (2024)
by: Mackenzie, Pierre, et al.
Published: (2024)
Bioinspired CNNs for border completion in occluded images
by: Coutinho, Catarina P., et al.
Published: (2026)
by: Coutinho, Catarina P., et al.
Published: (2026)
Controllable Hand Grasp Generation for HOI and Efficient Evaluation Methods
by: Ishant, et al.
Published: (2025)
by: Ishant, et al.
Published: (2025)
Parameter-Efficient Architectural Modifications for Translation-Invariant CNNs
by: Alabau-Bosque, Nuria, et al.
Published: (2026)
by: Alabau-Bosque, Nuria, et al.
Published: (2026)
Assessing the Alignment of Popular CNNs to the Brain for Valence Appraisal
by: Mertens, Laurent, et al.
Published: (2025)
by: Mertens, Laurent, et al.
Published: (2025)
The Quest for Universal Master Key Filters in DS-CNNs
by: Babaiee, Zahra, et al.
Published: (2025)
by: Babaiee, Zahra, et al.
Published: (2025)
Automatic Complementary Separation Pruning Toward Lightweight CNNs
by: Levin, David, et al.
Published: (2025)
by: Levin, David, et al.
Published: (2025)
Triggering hallucinations in model-based MRI reconstruction via adversarial perturbations
by: Buğday, Suna, et al.
Published: (2026)
by: Buğday, Suna, et al.
Published: (2026)
Joint Point Cloud Upsampling and Cleaning with Octree-based CNNs
by: Li, Jihe, et al.
Published: (2024)
by: Li, Jihe, et al.
Published: (2024)
Revising the Problem of Partial Labels from the Perspective of CNNs' Robustness
by: Zhang, Xin, et al.
Published: (2024)
by: Zhang, Xin, et al.
Published: (2024)
B-cos Alignment for Inherently Interpretable CNNs and Vision Transformers
by: Böhle, Moritz, et al.
Published: (2023)
by: Böhle, Moritz, et al.
Published: (2023)
On the universality of neural encodings in CNNs
by: Guth, Florentin, et al.
Published: (2024)
by: Guth, Florentin, et al.
Published: (2024)
Understanding CNNs from excitations
by: Ying, Zijian, et al.
Published: (2022)
by: Ying, Zijian, et al.
Published: (2022)
Adapting CNNs for Fisheye Cameras without Retraining
by: Griffiths, Ryan, et al.
Published: (2024)
by: Griffiths, Ryan, et al.
Published: (2024)
Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study
by: Mitra, Pallavi, et al.
Published: (2024)
by: Mitra, Pallavi, et al.
Published: (2024)
Data-Agnostic Face Image Synthesis Detection Using Bayesian CNNs
by: Leyva, Roberto, et al.
Published: (2024)
by: Leyva, Roberto, et al.
Published: (2024)
Understanding and Improving CNNs with Complex Structure Tensor: A Biometrics Study
by: Hernandez-Diaz, Kevin, et al.
Published: (2024)
by: Hernandez-Diaz, Kevin, et al.
Published: (2024)
Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment
by: Ganjdanesh, Alireza, et al.
Published: (2024)
by: Ganjdanesh, Alireza, et al.
Published: (2024)
Deep Network Pruning: A Comparative Study on CNNs in Face Recognition
by: Alonso-Fernandez, Fernando, et al.
Published: (2024)
by: Alonso-Fernandez, Fernando, et al.
Published: (2024)
Exploring Complementarity and Explainability in CNNs for Periocular Verification Across Acquisition Distances
by: Alonso-Fernandez, Fernando, et al.
Published: (2025)
by: Alonso-Fernandez, Fernando, et al.
Published: (2025)
Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods
by: Jiang, Mingqi, et al.
Published: (2022)
by: Jiang, Mingqi, et al.
Published: (2022)
CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection
by: Dey, Durjoy, et al.
Published: (2026)
by: Dey, Durjoy, et al.
Published: (2026)
Network transferability of adversarial patches in real-time object detection
by: Bayer, Jens, et al.
Published: (2024)
by: Bayer, Jens, et al.
Published: (2024)
Deep clustering using adversarial net based clustering loss
by: Lim, Kart-Leong
Published: (2024)
by: Lim, Kart-Leong
Published: (2024)
Game-invariant Features Through Contrastive and Domain-adversarial Learning
by: Kline, Dylan
Published: (2025)
by: Kline, Dylan
Published: (2025)
Automated Image Captioning with CNNs and Transformers
by: Cahyono, Joshua Adrian, et al.
Published: (2024)
by: Cahyono, Joshua Adrian, et al.
Published: (2024)
PDE-CNNs: Axiomatic Derivations and Applications
by: Bellaard, Gijs, et al.
Published: (2024)
by: Bellaard, Gijs, et al.
Published: (2024)
Post-hoc Self-explanation of CNNs
by: Boubekki, Ahcène, et al.
Published: (2026)
by: Boubekki, Ahcène, et al.
Published: (2026)
Similar Items
-
Towards properties of adversarial image perturbations
by: Kuznetsov, Egor, et al.
Published: (2025) -
Deep learning models are vulnerable, but adversarial examples are even more vulnerable
by: Li, Jun, et al.
Published: (2025) -
A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs
by: Stalder, Nicolas, et al.
Published: (2026) -
Investigating Market Strength Prediction with CNNs on Candlestick Chart Images
by: Duong, Thanh Nam, et al.
Published: (2025) -
D-LORD for Motion Stylization
by: Gupta, Meenakshi, et al.
Published: (2024)