8 citations · 14 across the 5 of their papers we have counts for
5 papers
Detecting Generated Images by Real Images Only
Xiuli Bi, Bo Liu, Fan Yang +4
As deep learning technology continues to evolve, the images yielded by generative models are becoming more and more realistic, triggering people to question the authenticity of ima…
Body and Head Orientation Estimation from Low-Resolution Point Clouds in Surveillance Settings
Onur N. Tepencelik, Wenchuan Wei, Pamela C. Cosman +1
We propose a system that estimates people's body and head orientations using low-resolution point cloud data from two LiDAR sensors. Our models make accurate estimations in real-wo…
A Neural Network Detector for Spectrum Sensing under Uncertainties
Ziyu Ye, Qihang Peng, Kelly Levick +4
Spectrum sensing is of critical importance in any cognitive radio system. When the primary user's signal has uncertain parameters, the likelihood ratio test, which is the theoretic…
Robust Deep Sensing Through Transfer Learning in Cognitive Radio
Qihang Peng, Andrew Gilman, Nuno Vasconcelos +2
We propose a robust spectrum sensing framework based on deep learning. The received signals at the secondary user's receiver are filtered, sampled and then directly fed into a conv…
Comparison of Neural Network Architectures for Spectrum Sensing
Ziyu Ye, Andrew Gilman, Qihang Peng +3
Different neural network (NN) architectures have different advantages. Convolutional neural networks (CNNs) achieved enormous success in computer vision, while recurrent neural net…