1 citations · 1 across the 6 of their papers we have counts for
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Self-Supervised Representation Learning for Adversarial Attack Detection
Yi Li, Plamen Angelov, Neeraj Suri
Supervised learning-based adversarial attack detection methods rely on a large number of labeled data and suffer significant performance degradation when applying the trained model…
PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection
Alvaro Lopez Pellcier, Yi Li, Plamen Angelov
Deepfake techniques generate highly realistic data, making it challenging for humans to discern between actual and artificially generated images. Recent advancements in deep learni…
UNICAD: A Unified Approach for Attack Detection, Noise Reduction and Novel Class Identification
Alvaro Lopez Pellicer, Kittipos Giatgong, Yi Li +2
As the use of Deep Neural Networks (DNNs) becomes pervasive, their vulnerability to adversarial attacks and limitations in handling unseen classes poses significant challenges. The…
Federated Adversarial Learning for Robust Autonomous Landing Runway Detection
Yi Li, Plamen Angelov, Zhengxin Yu +2
As the development of deep learning techniques in autonomous landing systems continues to grow, one of the major challenges is trust and security in the face of possible adversaria…