2 papers
cs.CV2025
Filtered-ViT: A Robust Defense Against Multiple Adversarial Patch Attacks
Aja Khanal, Ahmed Faid, Apurva Narayan
Deep learning vision systems are increasingly deployed in safety-critical domains such as healthcare, yet they remain vulnerable to small adversarial patches that can trigger miscl…
cs.LG2025
Federated Learning for Anomaly Detection in Energy Consumption Data: Assessing the Vulnerability to Adversarial Attacks
Yohannis Kifle Telila, Damitha Senevirathne, Dumindu Tissera +3
Anomaly detection is crucial in the energy sector to identify irregular patterns indicating equipment failures, energy theft, or other issues. Machine learning techniques for anoma…