[HTML][HTML] TC–Radar: Transformer–CNN Hybrid Network for Millimeter-Wave Radar Object Detection
In smart transportation, assisted driving relies on data integration from various sensors,
notably LiDAR and cameras. However, their optical performance can degrade under …
notably LiDAR and cameras. However, their optical performance can degrade under …
Using Deep Learning for Estimation of Objects Properties with Radar in Low Earth Orbits
MF Baysan - 2024 - mediatum.ub.tum.de
Radar technology has seen burgeoning applications across diverse domains, including
automotive industries and surveillance systems, thereby intertwining with everyday life …
automotive industries and surveillance systems, thereby intertwining with everyday life …
AdaPKC: PeakConv with Adaptive Peak Receptive Field for Radar Semantic Segmentation
T Li, L Zhang, Y Zhang, P Pi, Z Lu, Q Liao… - The Thirty-eighth Annual … - openreview.net
Deep learning-based radar detection technology is receiving increasing attention in areas
such as autonomous driving, UAV surveillance, and marine monitoring. Among recent …
such as autonomous driving, UAV surveillance, and marine monitoring. Among recent …
TARSS-Net: Temporal-Aware Radar Semantic Segmentation Network
Y Zhang, L Zhang, P Pi, T Li, Y Chen, S Peng… - The Thirty-eighth Annual … - openreview.net
Radar signal interpretation plays a crucial role in remote detection and ranging. With the
gradual display of the advantages of neural network technology in signal processing …
gradual display of the advantages of neural network technology in signal processing …
Improved Camera-Radar Fusion for Accurate Object Detection and Tracking in Autonomous Driving
L Shen - 2023 - search.proquest.com
In the realm of autonomous driving, the perception system stands at the forefront of vehicle
intelligence, enabling vehicles to interpret and react to their environment. To achieve this, a …
intelligence, enabling vehicles to interpret and react to their environment. To achieve this, a …