Copertina

Investigating and unmasking feature-level vulnerabilities of CNNs to adversarial perturbations

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Coppola, Davide, Lee, Hwee Kuan
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Towards properties of adversarial image perturbations
di: Kuznetsov, Egor, et al.
Pubblicazione: (2025)

Deep learning models are vulnerable, but adversarial examples are even more vulnerable
di: Li, Jun, et al.
Pubblicazione: (2025)

A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs
di: Stalder, Nicolas, et al.
Pubblicazione: (2026)

Investigating Market Strength Prediction with CNNs on Candlestick Chart Images
di: Duong, Thanh Nam, et al.
Pubblicazione: (2025)

D-LORD for Motion Stylization
di: Gupta, Meenakshi, et al.
Pubblicazione: (2024)

Designing Extremely Memory-Efficient CNNs for On-device Vision Tasks
di: Lee, Jaewook, et al.
Pubblicazione: (2024)

Partial Large Kernel CNNs for Efficient Super-Resolution
di: Lee, Dongheon, et al.
Pubblicazione: (2024)

OA-CNNs: Omni-Adaptive Sparse CNNs for 3D Semantic Segmentation
di: Peng, Bohao, et al.
Pubblicazione: (2024)

Reliable or Deceptive? Investigating Gated Features for Smooth Visual Explanations in CNNs
di: Mitra, Soham, et al.
Pubblicazione: (2024)

An adversarial feature learning based semantic communication method for Human 3D Reconstruction
di: Liu, Shaojiang, et al.
Pubblicazione: (2024)

Lightweight Channel Attention for Efficient CNNs
di: Kanaparthi, Prem Babu, et al.
Pubblicazione: (2026)

GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model
di: Zhu, Zhiyu, et al.
Pubblicazione: (2024)

CNNs for Style Transfer of Digital to Film Photography
di: Mackenzie, Pierre, et al.
Pubblicazione: (2024)

Bioinspired CNNs for border completion in occluded images
di: Coutinho, Catarina P., et al.
Pubblicazione: (2026)

Controllable Hand Grasp Generation for HOI and Efficient Evaluation Methods
di: Ishant, et al.
Pubblicazione: (2025)

Parameter-Efficient Architectural Modifications for Translation-Invariant CNNs
di: Alabau-Bosque, Nuria, et al.
Pubblicazione: (2026)

Assessing the Alignment of Popular CNNs to the Brain for Valence Appraisal
di: Mertens, Laurent, et al.
Pubblicazione: (2025)

The Quest for Universal Master Key Filters in DS-CNNs
di: Babaiee, Zahra, et al.
Pubblicazione: (2025)

Automatic Complementary Separation Pruning Toward Lightweight CNNs
di: Levin, David, et al.
Pubblicazione: (2025)

Triggering hallucinations in model-based MRI reconstruction via adversarial perturbations
di: Buğday, Suna, et al.
Pubblicazione: (2026)

Joint Point Cloud Upsampling and Cleaning with Octree-based CNNs
di: Li, Jihe, et al.
Pubblicazione: (2024)

Revising the Problem of Partial Labels from the Perspective of CNNs' Robustness
di: Zhang, Xin, et al.
Pubblicazione: (2024)

B-cos Alignment for Inherently Interpretable CNNs and Vision Transformers
di: Böhle, Moritz, et al.
Pubblicazione: (2023)

On the universality of neural encodings in CNNs
di: Guth, Florentin, et al.
Pubblicazione: (2024)

Understanding CNNs from excitations
di: Ying, Zijian, et al.
Pubblicazione: (2022)

Adapting CNNs for Fisheye Cameras without Retraining
di: Griffiths, Ryan, et al.
Pubblicazione: (2024)

Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study
di: Mitra, Pallavi, et al.
Pubblicazione: (2024)

Data-Agnostic Face Image Synthesis Detection Using Bayesian CNNs
di: Leyva, Roberto, et al.
Pubblicazione: (2024)

Understanding and Improving CNNs with Complex Structure Tensor: A Biometrics Study
di: Hernandez-Diaz, Kevin, et al.
Pubblicazione: (2024)

Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment
di: Ganjdanesh, Alireza, et al.
Pubblicazione: (2024)

Deep Network Pruning: A Comparative Study on CNNs in Face Recognition
di: Alonso-Fernandez, Fernando, et al.
Pubblicazione: (2024)

Exploring Complementarity and Explainability in CNNs for Periocular Verification Across Acquisition Distances
di: Alonso-Fernandez, Fernando, et al.
Pubblicazione: (2025)

Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods
di: Jiang, Mingqi, et al.
Pubblicazione: (2022)

CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection
di: Dey, Durjoy, et al.
Pubblicazione: (2026)

Network transferability of adversarial patches in real-time object detection
di: Bayer, Jens, et al.
Pubblicazione: (2024)

Deep clustering using adversarial net based clustering loss
di: Lim, Kart-Leong
Pubblicazione: (2024)

Game-invariant Features Through Contrastive and Domain-adversarial Learning
di: Kline, Dylan
Pubblicazione: (2025)

Automated Image Captioning with CNNs and Transformers
di: Cahyono, Joshua Adrian, et al.
Pubblicazione: (2024)

PDE-CNNs: Axiomatic Derivations and Applications
di: Bellaard, Gijs, et al.
Pubblicazione: (2024)

Post-hoc Self-explanation of CNNs
di: Boubekki, Ahcène, et al.
Pubblicazione: (2026)