no code implementations • CVPR 2018 • Qingchao Chen, Yang Liu, Zhaowen Wang, Ian Wassell, Kevin Chetty
In this paper, we propose the Re-weighted Adversarial Adaptation Network (RAAN) to reduce the feature distribution divergence and adapt the classifier when domain discrepancies are disparate.
Open-Ended Question Answering Unsupervised Domain Adaptation
no code implementations • 13 Nov 2018 • Lili Tao, Timothy Volonakis, Bo Tan, Yanguo Jing, Kevin Chetty, Melvyn Smith
We evaluate the proposed method on a state-of-the-art dataset and experimentally confirm that our approach outperforms the baseline method.
no code implementations • 13 Feb 2021 • Chong Tang, Wenda Li, Shelly Vishwakarma, Karl Woodbridge, Simon Julier, Kevin Chetty
However, noisy time-frequency spectrograms can significantly affect the performance of the classifier and must be tackled using appropriate denoising algorithms.
no code implementations • 2 Mar 2021 • Shelly Vishwakarma, Wenda Li, Chong Tang, Karl Woodbridge, Raviraj Adve, Kevin Chetty
We integrate WiFi transmission signals with the human animation data to generate the micro-Doppler features that incorporate the diversity of human motion characteristics, and the sensor parameters.
no code implementations • 9 Jul 2021 • Chong Tang, Wenda Li, Shelly Vishwakarma, Fangzhan Shi, Simon Julier, Kevin Chetty
On the other hand, we also propose a novel idea which trains a classifier with only simulated data and predicts new measured samples after cleaning them up with the FMNet.
no code implementations • 27 Jul 2021 • Shelly Vishwakarma, Wenda Li, Chong Tang, Karl Woodbridge, Raviraj Adve, Kevin Chetty
Further, we benchmark the data augmentation performance of the style transferred signatures with three other synthetic datasets -- clean simulated spectrograms (no environmental effects), simulated data with added AWGN noise, and simulated data with GAN generated noise.
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 • 11 Jan 2022 • Chong Tang, Wenda Li, Shelly Vishwakarma, Fangzhan Shi, Simon Julier, Kevin Chetty
It provides an effective solution to track human activities by reconstructing a skeleton model with 17 key points, which can assist with the interpretation of conventional RF sensing outputs in a more understandable way.
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 • 15 Mar 2023 • Yao Ge, Chong Tang, Haobo Li, Zikang Zhang, Wenda Li, Kevin Chetty, Daniele Faccio, Qammer H. Abbasi, Muhammad Imran
The dataset has been validated and has potential for the research of lip reading and multimodal speech recognition.