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 ...
The US Supreme Court questioned President Trump's tariff powers. This ruling highlights a major shift in economic power. Value now lies in data and software, not just physical goods. India must adapt ...
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: 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 ...