2 citations · 5 across the 6 of their papers we have counts for
6 papers
Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection
Zhongjie Ba, Qingyu Liu, Zhenguang Liu +4
Deepfake technology has given rise to a spectrum of novel and compelling applications. Unfortunately, the widespread proliferation of high-fidelity fake videos has led to pervasive…
FLTracer: Accurate Poisoning Attack Provenance in Federated Learning
Xinyu Zhang, Qingyu Liu, Zhongjie Ba +5
Federated Learning (FL) is a promising distributed learning approach that enables multiple clients to collaboratively train a shared global model. However, recent studies show that…
Locate and Verify: A Two-Stream Network for Improved Deepfake Detection
Chao Shuai, Jieming Zhong, Shuang Wu +6
Deepfake has taken the world by storm, triggering a trust crisis. Current deepfake detection methods are typically inadequate in generalizability, with a tendency to overfit to ima…
Learning in Dynamic Systems and Its Application to Adaptive PID Control
Omar Makke, Feng Lin
Deep learning using neural networks has revolutionized machine learning and put artificial intelligence into everyday life. In order to introduce self-learning to dynamic systems o…
Spectrum Sensing with Small-Sized Datasets in Cognitive Radio: Algorithms and Analysis
Feng Lin, Robert C. Qiu, James P. Browning
Spectrum sensing is a fundamental component of cognitive radio. How to promptly sense the presence of primary users is a key issue to a cognitive radio network. The time requiremen…
Generalized FMD Detection for Spectrum Sensing Under Low Signal-to-Noise Ratio
Feng Lin, Robert C. Qiu, Zhen Hu +3
Spectrum sensing is a fundamental problem in cognitive radio. We propose a function of covariance matrix based detection algorithm for spectrum sensing in cognitive radio network.…