/UrbanFlux

Code and data for the paper "A semi-supervised deep residual network for mode detection in Wi-Fi signals"

Primary LanguageJupyter Notebook

Urban Flux:

Ubiquitous sensors network for sensing multimodal traffic in real-time for complete streets.

General reference: "Farooq, B., Beaulieu, A., Ragab, M., Ba, V.T.(2015) Ubiquitous Monitoring of Pedestrian Dynamics: Exploring Wireless Ad Hoc Network of Multi-Sensor Technologies, IEEE SENSORS, Busan, Korea. November 2015."

Projects:

PLRDNN:

Code and data for the paper "Kalatian, A., Farooq, B. (2020) A semi-supervised deep residual network for mode detection in Wi-Fi signals. Big Data Analytics in Transportation. 2(2):1-14."

Aux_LSTM_PIE:

Codes for Aux_LSTM, trained on data extracted from video data of PIE dataset (https://github.com/aras62/PIEPredict).

preprint : https://arxiv.org/abs/2104.08123