Abstract: With the expansive deployment of ground base stations, low Earth orbit (LEO) satellites, and aerial platforms such as unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs), the ...

Abstract: Multimodal federated learning (FL) targets the intersection of two promising research directions in Internet of Things (IoT) scenarios: 1) leveraging complementary multimodal information to ...

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: Conventional fundamental frequency zero-sequence voltage (FFZSV) injection-based fault-tolerant operation methods cause power reversion under submodule (SM) failure conditions with low-power ...

Book Abstract: Electrical Engineering/Electromagnetics Waves and Fields in Inhomogeneous Media A Volume in the IEEE Press Series on Electromagnetic Waves Donald G ...