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pro vyhledávání: '"Alloulah, Mohammed"'
Autor:
Hao, Yiduo, Madani, Sohrab, Guan, Junfeng, Alloulah, Mohammed, Gupta, Saurabh, Hassanieh, Haitham
The perception of autonomous vehicles using radars has attracted increased research interest due its ability to operate in fog and bad weather. However, training radar models is hindered by the cost and difficulty of annotating large-scale radar data
Externí odkaz:
http://arxiv.org/abs/2312.04519
Autor:
Arnold, Maximilian, Alloulah, Mohammed
Deploying radio frequency (RF) localisation systems invariably entails non-trivial effort, particularly for the latest learning-based breeds. There has been little prior work on characterising and comparing how learnt localiser networks can be deploy
Externí odkaz:
http://arxiv.org/abs/2210.01930
Autor:
Alloulah, Mohammed, Arnold, Maximilian
Next generation cellular networks will implement radio sensing functions alongside customary communications, thereby enabling unprecedented worldwide sensing coverage outdoors. Deep learning has revolutionised computer vision but has had limited appl
Externí odkaz:
http://arxiv.org/abs/2206.06424
In future 6G cellular networks, a joint communication and sensing protocol will allow the network to perceive the environment, opening the door for many new applications atop a unified communication-perception infrastructure. However, interpreting th
Externí odkaz:
http://arxiv.org/abs/2111.02887
In this paper, we propose a new strategy for learning inertial robotic navigation models. The proposed strategy enhances the generalisability of end-to-end inertial modelling, and is aimed at wheeled robotic deployments. Concretely, the paper describ
Externí odkaz:
http://arxiv.org/abs/2106.15178
WiFi channel state information (CSI) has emerged as a plausible modality for sensing different human vital signs, i.e. respiration and body motion, as a function of modulated wireless signals that travel between WiFi devices. Although a remarkable pr
Externí odkaz:
http://arxiv.org/abs/2003.09386
Wi-Fi channel state information (CSI) has emerged as a plausible modality for sensing different human activities as a function of modulations in the wireless signal that travels between wireless devices. Until now, most research has taken a statistic
Externí odkaz:
http://arxiv.org/abs/1810.04302
Autor:
Alloulah, Mohammed
Context refers to a collection of elements with which people associate situations. The location and state of objects in an environment constitute an important subset of context, which has been thoroughly researched and established. By tracking the mo
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.587053
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