Papers
1–3 of 3Research Paper·Jan 15, 2026
Adversarial Evasion Attacks on Computer Vision using SHAP Values
The paper introduces a white-box attack on computer vision models using SHAP values. It demonstrates how adversarial evasion attacks can compromise the performance of deep learning models by reducing ...
5.0 viability
Research Paper·Feb 9, 2026
Generating Adversarial Events: A Motion-Aware Point Cloud Framework
Event cameras have been widely adopted in safety-critical domains such as autonomous driving, robotics, and human-computer interaction. A pressing challenge arises from the vulnerability of deep neura...
5.0 viability
Research Paper·Feb 26, 2026
Devling into Adversarial Transferability on Image Classification: Review, Benchmark, and Evaluation
Adversarial transferability refers to the capacity of adversarial examples generated on the surrogate model to deceive alternate, unexposed victim models. This property eliminates the need for direct ...
3.0 viability