most citedAutomotive Radar Interference Mitigation Using Adaptive Noise Canceller

118 citations · 200 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2020

mmFall: Fall Detection using 4D MmWave Radar and a Hybrid Variational RNN AutoEncoder

Feng Jin, Arindam Sengupta, Siyang Cao

In this paper we propose mmFall - a novel fall detection system, which comprises of (i) the emerging millimeter-wave (mmWave) radar sensor to collect the human body's point cloud a…

eess.SP2019

mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs

Arindam Sengupta, Feng Jin, Renyuan Zhang +1

In this paper, mm-Pose, a novel approach to detect and track human skeletons in real-time using an mmWave radar, is proposed. To the best of the authors' knowledge, this is the fir…

eess.SP2019118 cited

Automotive Radar Interference Mitigation Using Adaptive Noise Canceller

Feng Jin, Siyang Cao

Interference among frequency modulated continues wave automotive radars can either increase the noise floor, which occurs in the most cases, or generate a ghost target in rare situ…

eess.SP201980 cited

Multiple Patients Behavior Detection in Real-time using mmWave Radar and Deep CNNs

Feng Jin, Renyuan Zhang, Arindam Sengupta +4

To address potential gaps noted in patient monitoring in the hospital, a novel patient behavior detection system using mmWave radar and deep convolution neural network (CNN), which…

eess.SP20192 cited

MmWave Radar Point Cloud Segmentation using GMM in Multimodal Traffic Monitoring

Feng Jin, Arindam Sengupta, Siyang Cao +1

In multimodal traffic monitoring, we gather traffic statistics for distinct transportation modes, such as pedestrians, cars and bicycles, in order to analyze and improve people's d…