Abstract: The rapid pace of urbanization underscores the importance of waste monitoring and management in urban planning and environmental conservation. Remote sensing technology enables the aerial ...
Abstract: Integration of complementary information from different modalities and efficient computation is crucial in remote sensing (RS) image classification applications. Convolutional neural ...
Abstract: Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging ...
Abstract: Precise estimation of both state-of-charge (SoC) and state-of-health (SoH) is crucial for optimizing electric vehicle (EV) performance and enhancing the battery lifetime, safety, and ...
Abstract: In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models ...
Abstract: This study investigates the impact of artificial general intelligence (AGI)-assisted project-based learning (PBL) on students’ higher order thinking and self-efficacy. Based on input from 17 ...
Book Abstract: Electrical Engineering Wave Propagation and Scattering in Random Media A volume in the IEEE/OUP Series on Electromagnetic Wave Theory Donald G. Dudley, Series Editor This IEEE Classic ...
Abstract: In this study, we address a gap in existing unsupervised domain adaptation approaches on LiDAR-based 3D object detection, which have predominantly concentrated on adapting between ...
Book Abstract: Electrical Engineering/Electromagnetics Waves and Fields in Inhomogeneous Media A Volume in the IEEE Press Series on Electromagnetic Waves Donald G ...
Abstract: Accurate tropospheric delay forecasts are imperative for microwave-based remote sensing techniques, playing a pivotal role in early warning and forecasting of natural disasters such as ...
Abstract: Offset-based representation has emerged as a promising approach for modeling semantic relations between pixels and object motion, demonstrating efficacy across various computer vision tasks.
Abstract: Accurate pedestrian trajectory prediction is a crucial task for ensuring the safety of autonomous driving. However, most of the existing methods only model pedestrian trajectories in the ...