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Simultaneous Localization and Mapping

Simultaneous localization and mapping (SLAM) is the task of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

( Image credit: ORB-SLAM2 )

Papers

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Showing 151–160 of 572 papers

TitleStatusHype
Deep Learning Reforms Image Matching: A Survey and Outlook—0
Deep Learning for Visual Localization and Mapping: A Survey—0
Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology—0
A Belief Propagation Approach for Direct Multipath-Based SLAM—0
Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications—0
Deep-Learning-Based Indoor Human Following of Mobile Robot Using Color Feature—0
Augmented Reality for Depth Cues in Monocular Minimally Invasive Surgery—0
Deep Learning-based Cooperative LiDAR Sensing for Improved Vehicle Positioning—0
A Two-stage Unsupervised Approach for Low light Image Enhancement—0
A Geometric Nonlinear Stochastic Filter for Simultaneous Localization and Mapping—0
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