Multiple-Input–Multiple-Output Radar (MIMO)

Deep Learning-Based In-Cabin Monitoring and Vehicle Safety System Using a 4-D Imaging Radar Sensor
We propose a 2-D CNN-LSTM deep learning model that uses a MIMO radar to accurately detect, count, and classify passengers in five-seater vehicles, achieving over 95% accuracy in detecting unattended infants/children, 89% accuracy in counting passengers and identifying their seats, and 74% accuracy in classifying passengers, demonstrating its applicability in any five-seater vehicle.
Hajar Abedi, Martin Ma, James He, Jennifer Yu, Ahmad Ansariyan, George Shaker
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Deep Learning-Based In-Cabin Monitoring and Vehicle Safety System Using a 4-D Imaging Radar Sensor
On the Use of Machine Learning and Deep Learning for Radar- Based Passenger Monitoring
In the past decade, there has been an increasing demand for in-vehicle safety sensors. In this paper, we use a multi-input multi-output …
Hajar Abedi, Martin Ma, Jennifer Yu, James He, Ahmad Ansariyan, George Shaker
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On the Use of Machine Learning and Deep Learning for Radar- Based Passenger Monitoring