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Radar-camera fusion for object detection and semantic segmentation in autonomous driving: A comprehensive review
Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …
Dpft: Dual perspective fusion transformer for camera-radar-based object detection
The perception of autonomous vehicles has to be efficient, robust, and cost-effective.
However, cameras are not robust against severe weather conditions, lidar sensors are …
However, cameras are not robust against severe weather conditions, lidar sensors are …
Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey
K Shi, S He, Z Shi, A Chen, Z **
MP Ronecker, X Diaz, M Karner… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
This paper introduces a novel hybrid architecture that enhances radar-based Dynamic
Occupancy Grid Map** (DOGM) for autonomous vehicles, integrating deep learning for …
Occupancy Grid Map** (DOGM) for autonomous vehicles, integrating deep learning for …
Exploiting sparsity in automotive radar object detection networks
Having precise perception of the environment is crucial for ensuring the secure and reliable
functioning of autonomous driving systems. Radar object detection networks are one …
functioning of autonomous driving systems. Radar object detection networks are one …
RCF-TP: Radar-Camera Fusion with Temporal Priors for 3D Object Detection
Sensor fusion is an important method for achieving robust perception systems in
autonomous driving, Internet of things, and robotics. Most multi-modal 3D detection models …
autonomous driving, Internet of things, and robotics. Most multi-modal 3D detection models …
A novel chaining-based indirect addressing mode in a vertical vector processor
Efficient processing architectures for irregular data patterns require vector element
addressing with flexible indices. Therefore, state-of-the-art SIMD vector extensions …
addressing with flexible indices. Therefore, state-of-the-art SIMD vector extensions …
DSFEC: Efficient and Deployable Deep Radar Object Detection
G Dandugula, S Boddana, S Mirashi - arxiv preprint arxiv:2412.07411, 2024 - arxiv.org
Deploying radar object detection models on resource-constrained edge devices like the
Raspberry Pi poses significant challenges due to the large size of the model and the limited …
Raspberry Pi poses significant challenges due to the large size of the model and the limited …