6 papers
HQ-MPSD: A Multilingual Artifact-Controlled Benchmark for Partial Deepfake Speech Detection
Menglu Li, Majd Alber, Ramtin Asgarianamiri +2
Detecting partial deepfake speech is challenging because manipulations occur only in short regions while the surrounding audio remains authentic. However, existing detection method…
QLook:Quantum-Driven Viewport Prediction for Virtual Reality
Niusha Sabri Kadijani, Yoga Suhas Kuruba Manjunath, Xiaodan Bi +1
We propose QLook, a quantum-driven predictive framework to improve viewport prediction accuracy in immersive virtual reality (VR) environments. The framework utilizes quantum neura…
Frame-level Temporal Difference Learning for Partial Deepfake Speech Detection
Menglu Li, Xiao-Ping Zhang, Lian Zhao
Detecting partial deepfake speech is essential due to its potential for subtle misinformation. However, existing methods depend on costly frame-level annotations during training, l…
ResLearn: Transformer-based Residual Learning for Metaverse Network Traffic Prediction
Yoga Suhas Kuruba Manjunath, Mathew Szymanowski, Austin Wissborn +3
Our work proposes a comprehensive solution for predicting Metaverse network traffic, addressing the growing demand for intelligent resource management in eXtended Reality (XR) serv…
Discern-XR: An Online Classifier for Metaverse Network Traffic
Yoga Suhas Kuruba Manjunath, Austin Wissborn, Mathew Szymanowski +3
In this paper, we design an exclusive Metaverse network traffic classifier, named Discern-XR, to help Internet service providers (ISP) and router manufacturers enhance the quality…
Time-Distributed Feature Learning for Internet of Things Network Traffic Classification
Yoga Suhas Kuruba Manjunath, Sihao Zhao, Xiao-Ping Zhang +1
Deep learning-based network traffic classification (NTC) techniques, including conventional and class-of-service (CoS) classifiers, are a popular tool that aids in the quality of s…