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.
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 • 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.
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 • 18 Mar 2021 • Yordanka Karayaneva, Sara Sharifzadeh, Wenda Li, Yanguo Jing, Bo Tan
This study proposes two unsupervised feature extraction methods for the purpose of human activity monitoring using Doppler-streams.
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 • 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.
1 code implementation • 15 Jan 2021 • Yuhuai Wu, Markus Rabe, Wenda Li, Jimmy Ba, Roger Grosse, Christian Szegedy
While designing inductive bias in neural architectures has been widely studied, we hypothesize that transformer networks are flexible enough to learn inductive bias from suitable generic tasks.
1 code implementation • ICLR 2021 • Wenda Li, Lei Yu, Yuhuai Wu, Lawrence C. Paulson
In this paper, we present a benchmark for high-level mathematical reasoning and study the reasoning capabilities of neural sequence-to-sequence models.