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Sensor Fusion

Sensor fusion is the process of combining sensor data or data derived from disparate sources such that the resulting information has less uncertainty than would be possible when these sources were used individually. [Wikipedia]

Papers

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Showing 221–230 of 509 papers

TitleStatusHype
Sense, Imagine, Act: Multimodal Perception Improves Model-Based Reinforcement Learning for Head-to-Head Autonomous Racing—0
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous drivingCode1
Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object DetectionCode1
Group Equivariant BEV for 3D Object Detection—0
Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving—0
A Preliminary Study of Deep Learning Sensor Fusion for Pedestrian DetectionCode0
Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive ReviewCode2
In-situ surface porosity prediction in DED (directed energy deposition) printed SS316L parts using multimodal sensor fusion—0
TransFusionOdom: Interpretable Transformer-based LiDAR-Inertial Fusion Odometry EstimationCode1
Survey on LiDAR Perception in Adverse Weather Conditions—0
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