This study devises an innovative LiDAR point cloud down-sampling strategy that capitalizes on the properties of Fuzzy C Means (FCM) clustering membership functions in each dimension. Traditional ...

Abstract: Local sampling plays a key role in modeling 3D point clouds. Due to the disordered and unstructured nature of point cloud data, conventional 3D deep models such as PointNet++ and its ...

Abstract: We propose an end-to-end attribute compression method for dense point clouds. The proposed method combines a frequency sampling module, an adaptive scale feature extraction module with ...

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Rock-chip sampling by Nelson Resources (ASX: NES) at its newly acquired Gold Point project in the US state of Nevada has returned spectacular grades of up to 32.7 grams per tonne gold and 574g/t ...

Abstract: Given that the sampling and arrangement of the array need a reasonable standard to guide in high-precision magnetocardiography (MCG) imaging, the sampling range required for robust ...

ABSTRACT: In many real-time resource-constrained embedded systems, highly-predictable system behavior is a key design requirement. The “time-triggered co-operative” (TTC) scheduling algorithm provides ...

Abstract: Point cloud processing is fundamental to applications such as autonomous driving, robotic navigation, and 3D reconstruction. Sampling is a crucial process in point cloud processing, but ...

Abstract: Low sampling frequency challenges the exact identification of continuous-time (CT) dynamical systems from sampled data, even when their models are identifiable. A necessary and sufficient ...

Abstract: Implicit Neural Representations (INRs), capable of learning the mapping between sampling coordinates and occupancy statuses to effectively represent 3D content, are increasingly adopted in ...