no code implementations • 10 Oct 2023 • Jingzhi Hu, Zhe Chen, Tianyue Zheng, Robert Schober, Jun Luo
Our simulation results confirm that HoloFed achieves a 57% lower positioning error variance compared to a beam-scanning baseline and can effectively adapt to diverse environments.
1 code implementation • ICCV 2023 • Shujie Zhang, Tianyue Zheng, Zhe Chen, Jingzhi Hu, Abdelwahed Khamis, Jiajun Liu, Jun Luo
To overcome the challenge in labeling RF imaging given its human incomprehensible nature, OCHID-Fi employs a cross-modality and cross-domain training process.
no code implementations • 17 Feb 2023 • Tianyue Zheng, Ang Li, Zhe Chen, Hongbo Wang, Jun Luo
Object detection with on-board sensors (e. g., lidar, radar, and camera) play a crucial role in autonomous driving (AD), and these sensors complement each other in modalities.
no code implementations • 1 Dec 2021 • Tianyue Zheng, Zhe Chen, Shuya Ding, Chao Cai, Jun Luo
Whereas adversarial training can be useful against specific adversarial perturbations, they have also proven ineffective in generalizing towards attacks deviating from those used for training.
no code implementations • 16 Nov 2021 • Tianyue Zheng, Zhe Chen, Shujie Zhang, Chao Cai, Jun Luo
Crucial for healthcare and biomedical applications, respiration monitoring often employs wearable sensors in practice, causing inconvenience due to their direct contact with human bodies.
1 code implementation • 29 Oct 2021 • Shuya Ding, Zhe Chen, Tianyue Zheng, Jun Luo
Radio-Frequency (RF) based device-free Human Activity Recognition (HAR) rises as a promising solution for many applications.
no code implementations • 28 Oct 2021 • Tianyue Zheng, Zhe Chen, Chao Cai, Jun Luo, Xu Zhang
Given the significant amount of time people spend in vehicles, health issues under driving condition have become a major concern.
no code implementations • 28 Oct 2021 • Tianyue Zheng, Zhe Chen, Shuya Ding, Jun Luo
To better understand this potential, this article takes a layered approach to summarize RF sensing enabled by deep learning.
no code implementations • 27 Oct 2021 • Tianyue Zheng, Zhe Chen, Jun Luo, Lin Ke, Chaoyang Zhao, Yaowen Yang
To this end, we equip SiWa with a deep learning pipeline to parse the rich sensory data.
no code implementations • 29 Sep 2021 • Shujie Zhang, Tianyue Zheng, Zhe Chen, Jun Luo, Sinno Pan
In many practical scenarios of signal extraction from a nonlinear mixture, only one (signal) source is intended to be extracted.
no code implementations • 28 Aug 2017 • Tianyue Zheng, Weihong Deng, Jiani Hu
Labeled Faces in the Wild (LFW) database has been widely utilized as the benchmark of unconstrained face verification and due to big data driven machine learning methods, the performance on the database approaches nearly 100%.