Echoes beyond points: Unleashing the power of raw radar data in multi-modality fusion
Radar is ubiquitous in autonomous driving systems due to its low cost and good adaptability
to bad weather. Nevertheless, the radar detection performance is usually inferior because its …
to bad weather. Nevertheless, the radar detection performance is usually inferior because its …
Deep-neural-network-enabled vehicle detection using high-resolution automotive radar imaging
Advanced driver assistance systems (ADASs) and autonomous vehicles rely on different
types of sensors, such as camera, radar, ultrasonic, and LiDAR, to sense the surrounding …
types of sensors, such as camera, radar, ultrasonic, and LiDAR, to sense the surrounding …
Bootstrapping Autonomous Driving Radars with Self-Supervised Learning
The perception of autonomous vehicles using radars has attracted increased research
interest due its ability to operate in fog and bad weather. However training radar models is …
interest due its ability to operate in fog and bad weather. However training radar models is …
Bootstrapping Autonomous Radars with Self-Supervised Learning
The perception of autonomous vehicles using radars has attracted increased research
interest due its ability to operate in fog and bad weather. However, training radar models is …
interest due its ability to operate in fog and bad weather. However, training radar models is …
Exploiting virtual array diversity for accurate radar detection
Using millimeter-wave radars as a perception sensor provides self-driving cars with robust
sensing capability in adverse weather. However, mmWave radars currently lack sufficient …
sensing capability in adverse weather. However, mmWave radars currently lack sufficient …
Time-sensitive and distance-tolerant deep learning-based vehicle detection using high-resolution radar bird's-eye-view images
Advanceddriver assistance systems (ADASs) and autonomous vehicles rely on
differenttypes of sensors, such as cameras, radar, ultrasonic, and LiDAR to sense …
differenttypes of sensors, such as cameras, radar, ultrasonic, and LiDAR to sense …
ARC: Automotive Radar Consistency Regularization for Semi-Supervised Learning
In recent years, radar has become a crucial part of road scene perception. In particular,
radar increases sensing reliability in poor weather and lighting conditions. State-of-the-art …
radar increases sensing reliability in poor weather and lighting conditions. State-of-the-art …
Auto Signal Generate in Curvy Roads Using Object Detection
Sharp turns or dangerous roadway bends cause most car accidents today. These vehicle
accidents usually cause death or permanent disability. Reckless driving on curves causes …
accidents usually cause death or permanent disability. Reckless driving on curves causes …
Enabling Visual Recognition at Radio Frequency
This paper introduces PanoRadar, a novel RF imaging system that brings RF resolution
close to that of LiDAR, while providing resilience against conditions challenging for optical …
close to that of LiDAR, while providing resilience against conditions challenging for optical …
Redefining Automotive Radar Imaging: A Domain-Informed 1D Deep Learning Approach for High-Resolution and Efficient Performance
Millimeter-wave (mmWave) radars are indispensable for perception tasks of autonomous
vehicles, thanks to their resilience in challenging weather conditions. Yet, their deployment …
vehicles, thanks to their resilience in challenging weather conditions. Yet, their deployment …