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Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review [PDF]
Sensors, 2021 With the significant advancement of sensor and communication technology and the reliable application of obstacle detection techniques and algorithms, automated driving is becoming a pivotal technology that can revolutionize the future of transportation ...
De Jong Yeong +3 more
doaj +6 more sources
Transformer-Based Sensor Fusion for Autonomous Driving: A Survey [PDF]
arXiv, 2023 Sensor fusion is an essential topic in many perception systems, such as autonomous driving and robotics. Transformers-based detection head and CNN-based feature encoder to extract features from raw sensor-data has emerged as one of the best performing sensor-fusion 3D-detection-framework, according to the dataset leaderboards.
Apoorv Singh
arxiv +3 more sources
Radar Voxel Fusion for 3D Object Detection [PDF]
Applied Sciences, 2021 Automotive traffic scenes are complex due to the variety of possible scenarios, objects, and weather conditions that need to be handled. In contrast to more constrained environments, such as automated underground trains, automotive perception systems ...
Felix Nobis +4 more
doaj +2 more sources
City Data Fusion: Sensor Data Fusion in the Internet of Things [PDF]
arXiv, 2015 Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor ...
Charith Perera +6 more
arxiv +3 more sources
An Outline of Multi-Sensor Fusion Methods for Mobile Agents Indoor Navigation
Sensors, 2021 Indoor autonomous navigation refers to the perception and exploration abilities of mobile agents in unknown indoor environments with the help of various sensors. It is the basic and one of the most important functions of mobile agents.
Yuanhao Qu +5 more
doaj +2 more sources
Robust Deep Multi-Modal Sensor Fusion using Fusion Weight Regularization and Target Learning [PDF]
arXiv, 2019 Sensor fusion has wide applications in many domains including health care and autonomous systems. While the advent of deep learning has enabled promising multi-modal fusion of high-level features and end-to-end sensor fusion solutions, existing deep learning based sensor fusion techniques including deep gating architectures are not always resilient ...
Li, Peng +5 more
arxiv +3 more sources
Fingerprint verification by fusion of optical and capacitive sensors [PDF]
, 2004 A few works have been presented so far on information fusion for fingerprint verification. None, however, have explicitly investigated the use of multi-sensor fusion, in other words, the integration of the information provided by multiple devices to ...
MARCIALIS, GIAN LUCA, ROLI, FABIO
core +3 more sources
Deep learning empowered sensor fusion boosts infant movement classification [PDF]
Communications MedicineBackground To assess the integrity of the developing nervous system, the Prechtl general movement assessment (GMA) is recognized for its clinical value in diagnosing neurological impairments in early infancy.
Tomas Kulvicius +10 more
doaj +2 more sources
Exploring the Unseen: A Survey of Multi-Sensor Fusion and the Role of Explainable AI (XAI) in Autonomous Vehicles [PDF]
SensorsAutonomous vehicles (AVs) rely heavily on multi-sensor fusion to perceive their environment and make critical, real-time decisions by integrating data from various sensors such as radar, cameras, Lidar, and GPS.
De Jong Yeong +2 more
doaj +2 more sources
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation [PDF]
IEEE International Conference on Robotics and Automation, 2022 Multi-sensor fusion is essential for an accurate and reliable autonomous driving system. Recent approaches are based on point-level fusion: augmenting the LiDAR point cloud with camera features.
Zhijian Liu +6 more
semanticscholar +1 more source