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Found 4 papers, 0 papers with code
Efficient divide-and-conquer registration of UAV and ground LiDAR point clouds through canopy shape context
Finally, we implement coarse alignment of ULS and ground LiDAR datasets by combining the results of ground alignment and image matching and finish fine registration.
Incorporating Orientations into End-to-end Driving Model for Steering Control
In this paper, we present a novel end-to-end deep neural network model for autonomous driving that takes monocular image sequence as input, and directly generates the steering control angle.
Transport based Graph Kernels
In order to effectively utilize graph hierarchical structure information, we propose pyramid graph kernel based on optimal transport (OT).
SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction
Generative Adversarial Networks (GANs) are powerful tools for reconstructing Compressed Sensing Magnetic Resonance Imaging (CS-MRI).
