Skip to content

This dataset refers to the paper https://arxiv.org/abs/2306.17062. The dataset consists of beam SNR samples corresponding to set of 10 gestures across three people and two environments

Notifications You must be signed in to change notification settings

nisarnabeel/mmWave-CSI-dataset-60-GHz-for-gesture-recognition

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 

Repository files navigation

mmWave-beam SNR-dataset-60-GHz-for-gesture-recognition

This dataset refers to the paper https://arxiv.org/abs/2306.17062. The dataset consists of beam SNR samples corresponding to a set of 10 gestures across three people and two environments. if you find this work useful, please cite the original article N. N. Bhat, R. Berkvens and J. Famaey, "Gesture Recognition with mmWave Wi-Fi Access Points: Lessons Learned," 2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Boston, MA, USA, 2023, pp. 127-136, doi: 10.1109/WoWMoM57956.2023.00027. or Nabeel Nisar Bhat. (2023). Gesture Recognition with mmWave Wi-Fi Access Points: Lessons Learned~Dataset [Data set]. 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) (IEEE WoWMoM 2023).

The dataset is here https://zenodo.org/records/7813244

About

This dataset refers to the paper https://arxiv.org/abs/2306.17062. The dataset consists of beam SNR samples corresponding to set of 10 gestures across three people and two environments

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published