no code implementations • 13 Oct 2023 • Ahmed Khalil, Robert Piechocki, Raul Santos-Rodriguez
In this paper we introduce learnable lattice vector quantization and demonstrate its effectiveness for learning discrete representations.
no code implementations • 13 Sep 2022 • Hakan Erdol, Xiaoyang Wang, Peizheng Li, Jonathan D. Thomas, Robert Piechocki, George Oikonomou, Rui Inacio, Abdelrahim Ahmad, Keith Briggs, Shipra Kapoor
In order to provide such services, 5G systems will support various combinations of access technologies such as LTE, NR, NR-U and Wi-Fi.
no code implementations • 31 Aug 2022 • Peizheng Li, Hakan Erdol, Keith Briggs, Xiaoyang Wang, Robert Piechocki, Abdelrahim Ahmad, Rui Inacio, Shipra Kapoor, Angela Doufexi, Arjun Parekh
The model will also be used as the base model for adaptive training in the new environment.
no code implementations • 27 Jun 2022 • Peizheng Li, Xiaoyang Wang, Robert Piechocki, Shipra Kapoor, Angela Doufexi, Arjun Parekh
Measuring customer experience on mobile data is of utmost importance for global mobile operators.
no code implementations • 8 Jun 2022 • Peizheng Li, Jonathan Thomas, Xiaoyang Wang, Hakan Erdol, Abdelrahim Ahmad, Rui Inacio, Shipra Kapoor, Arjun Parekh, Angela Doufexi, Arman Shojaeifard, Robert Piechocki
One of the main reasons is the modelling gap between the simulation and the real environment, which could make the RL agent trained by simulation ill-equipped for the real environment.
no code implementations • 13 Apr 2022 • Bo Tan, Alison Burrows, Robert Piechocki, Ian Craddock, Karl Woodbridge, Kevin Chetty
The experiment results offer potential for promising healthcare applications using Wi-Fi passive sensing in the home to monitor daily activities, to gather health data and detect emergency situations.
no code implementations • 12 Nov 2021 • Peizheng Li, Jonathan Thomas, Xiaoyang Wang, Ahmed Khalil, Abdelrahim Ahmad, Rui Inacio, Shipra Kapoor, Arjun Parekh, Angela Doufexi, Arman Shojaeifard, Robert Piechocki
We provide a taxonomy for the challenges faced by ML/RL models throughout the development life-cycle: from the system specification to production deployment (data acquisition, model design, testing and management, etc.).
1 code implementation • 8 Oct 2021 • Mohammud J. Bocus, Wenda Li, Shelly Vishwakarma, Roget Kou, Chong Tang, Karl Woodbridge, Ian Craddock, Ryan McConville, Raul Santos-Rodriguez, Kevin Chetty, Robert Piechocki
This dataset can be exploited to advance WiFi and vision-based HAR, for example, using pattern recognition, skeletal representation, deep learning algorithms or other novel approaches to accurately recognize human activities.
no code implementations • 8 Mar 2021 • Peizheng Li, Han Cui, Aftab Khan, Usman Raza, Robert Piechocki, Angela Doufexi, Tim Farnham
Finally, an ablation study of the training dataset shows that, in both office and sport hall scenarios, after reusing the feature extraction layers of the base model, only 55% of the training data is required to obtain the models' accuracy similar to the base models.
no code implementations • 16 Oct 2020 • Peizheng Li, Han Cui, Aftab Khan, Usman Raza, Robert Piechocki, Angela Doufexi, Tim Farnham
Meanwhile, using a well-organised architecture, the neural network models can be trained directly with raw data from the CSI and localisation features can be automatically extracted to achieve accurate position estimates.
2 code implementations • 25 Jun 2018 • Ryan McConville, Gareth Archer, Ian Craddock, Herman ter Horst, Robert Piechocki, James Pope, Raul Santos-Rodriguez
In this paper we study the prediction of heart rate from acceleration using a wrist worn wearable.