Abstract: Fault diagnosis of railway assets has drawn the interest of both the scholarly and engineering communities. Federated learning (FL) enables training models across distributed assets to ...
Abstract: Quantum Computing (QC) technology and Deep Learning (DL) science have garnered significant attention for their potential to revolutionize computation. This paper introduces the basic ...
Abstract: The increasing AI applications demands efficient computing capabilities to support a huge amount of calculations. Among the related arithmetic operations, multiplication is an indispensable ...
Abstract: The semantic segmentation network performance of large-scale outdoor point clouds is usually limited by the number of input point clouds. In the application of most methods, the point cloud ...
Abstract: Self-supervised learning of point cloud aims to leverage unlabeled 3D data to learn meaningful representations without reliance on manual annotations. However, current approaches face ...
Abstract: Masked autoencoder (MAE) is a recently widely used self-supervised learning method that has achieved great success in NLP and computer vision. However, the potential advantages of masked pre ...
Abstract: As radar can directly provide the velocity of the targets in autonomous driving and is known for the robustness against adverse weather conditions, it plays an important role in contrast to ...
A secure GUI-based banking application built with Java Swing and SQLite using NetBeans IDE. This project demonstrates how to integrate desktop applications with a database to manage financial ...
Abstract: Contribution: This study identifies the types of interaction that contribute to student learning with student-led tutorials (SLTs). The quality of these interactions include peer discussion, ...