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: 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: Autonomous underwater vehicles (AUV) play an important role in the process of human exploration of the ocean. However, the existing AUV control methods are faced with the problem of ...
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 ...
In this tutorial, we present an advanced, hands-on tutorial that demonstrates how we use Qrisp to build and execute non-trivial quantum algorithms. We walk through core Qrisp abstractions for quantum ...
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: In this paper, we propose three modular multiplication algorithms that use only the IEEE 754 binary floating-point operations. Several previous studies have used floating-point operations to ...
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 ...
Adam Mosseri is just looking for the guy who did this. Adam Mosseri is just looking for the guy who did this. is a senior reviewer with over a decade of experience writing about consumer tech. She has ...
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