Abstract: Photovoltaic arrays receive varying levels of solar radiation due to factors such as shadows created by clouds, surrounding buildings, and other obstructions. Therefore, an effective Maximum ...
Abstract: Point cloud registration is a key computer vision task that must be solved in most modern pipelines for 3-D data processing. Iterative Closest Point (ICP) algorithms are one of the most ...
Abstract: In this work, we propose a voxel-based single-stage fine-grained and efficient point cloud 3D object detection algorithm to address the inadequate granularity in point cloud feature ...
Abstract: Normal estimation is a critical task in point cloud analysis, especially in cultural heritage preservation and digitization. However, due to errors from acquisition devices and environmental ...
Abstract: Mobile robots rely on Visual Simultaneous Localization and Mapping (SLAM) as their primary technology. However, in environments with dynamic lighting changes, current state-of-the-art visual ...
Abstract: LiDAR is one of the most promising scanning technologies with a wide range of applications. It is commonly used for geodetic and cartographic tasks, allowing for the scanning and ...
Abstract: The Tomasulo algorithm is a computer architecture hardware algorithm used for dynamic scheduling of instruction. The reservation station changes the read-write control mechanism of the ...
Abstract: The fixed-point iteration method is widely used in electromagnetic field analysis involving hysteresis property due to its strong robustness, but it has the problem of low computational ...
Abstract: Point-cloud registration and stitching are important topics in the field of robot navigation and 3D reconstruction, e.g., the accuracy of point cloud registration and stitching in robot ...
Abstract: With the continuous development of urban traffic and the improvement of intelligent transportation systems, the accurate extraction and analysis of road traffic markings becomes more and ...
Abstract: Conventional time-of-arrival localization methods often suffer from performance degradation in the presence of outliers. To address this issue, a robust framework is proposed to mitigate the ...
Abstract: Change point detection (CPD) is a valuable technique in time series (TS) analysis, which allows for the automatic detection of abrupt variations within the TS. It is often useful in ...
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