Search Results for author:
Found 8 papers, 4 papers with code
Vision meets mmWave Radar: 3D Object Perception Benchmark for Autonomous Driving
This kind of radar format can enable machine learning models to generate more reliable object perception results after interacting and fusing the information or features between the camera and radar.
Learning to Detect Open Carry and Concealed Object with 77GHz Radar
Detecting harmful carried objects plays a key role in intelligent surveillance systems and has widespread applications, for example, in airport security.
Perception Through 2D-MIMO FMCW Automotive Radar Under Adverse Weather
Millimeter-wave (mmWave) radars are being increasingly integrated in commercial vehicles to support new Adaptive Driver Assisted Systems (ADAS) features that require accurate location and Doppler velocity estimates of objects, independent of environmental conditions.
RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization
Finally, we propose a method to evaluate the object detection performance of the RODNet.
MIMO-SAR: A Hierarchical High-resolution Imaging Algorithm for mmWave FMCW Radar in Autonomous Driving
Millimeter-wave radars are being increasingly integrated into commercial vehicles to support advanced driver-assistance system features.
RAMP-CNN: A Novel Neural Network for Enhanced Automotive Radar Object Recognition
Millimeter-wave radars are being increasingly integrated into commercial vehicles to support new advanced driver-assistance systems by enabling robust and high-performance object detection, localization, as well as recognition - a key component of new environmental perception.
RODNet: Radar Object Detection Using Cross-Modal Supervision
Radar is usually more robust than the camera in severe driving scenarios, e. g., weak/strong lighting and bad weather.
Experiments with mmWave Automotive Radar Test-bed
Millimeter-wave (mmW) radars are being increasingly integrated in commercial vehicles to support new Adaptive Driver Assisted Systems (ADAS) for its ability to provide high accuracy location, velocity, and angle estimates of objects, largely independent of environmental conditions.
