Many visions of 6G and the evolution of data rates in wireless systems in general are directing their vectors toward Tbps communications by 2030. This target, with the important goal of [...]
We present a deep learning framework for video classification applicable to face recognition and dynamic texture recognition. A Deep Autoencoder Network Template (DANT) is designed whose [...]
This paper applies the principles of Virtual Reality (VR) to robots, rather than living organisms. A simulator, of either physical states or information states, renders outputs to custom [...]
In this paper, we consider the framework of partitioned edge learning for iteratively training a large-scale model using many resource-constrained devices (called workers). To this end, in [...]
Integrating LEO Satellite and UAV Relaying via Reinforcement Learning for Non-Terrestrial Networks
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A mega-constellation of low-earth orbit (LEO) satellites has the potential to enable long-range communication with low latency. Integrating this with burgeoning unmanned aerial vehicle (UAV) [...]
Distributional Reinforcement Learning for mmWave Communications with Intelligent Reflectors on a UAV
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In this paper, a novel communication framework that uses an unmanned aerial vehicle (UAV)-carried intelligent reflector (IR) is proposed to enhance multi-user downlink transmissions over [...]
Cellular-connected wireless connectivity provides new opportunities for virtual reality (VR) to offer seamless user experience from anywhere at anytime. To realize this vision, the [...]
Face anti-spoofing (FAS) plays a vital role in face recognition systems. Most state-of-the-art FAS methods 1) rely on stacked convolutions and expert-designed network, which is weak in [...]
An online game of chess against a human opponent appears to be indistinguishable from a game against a machine: both happen on the screen. Yet, people prefer to play chess against other people [...]
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks. Existing multi-modal FAS methods rely on stacked vanilla convolutions, which is weak [...]
