Abstract: The past decade has seen an explosion in the amount of digital information stored in electronic health records (EHRs). While primarily designed for archiving patient information and ...
Abstract: This letter presents two new change detection (CD) methods for synthetic aperture radar (SAR) image stacks based on the Neyman–Pearson criterion. The first proposed method uses the data from ...
Abstract: Lithium ion batteries should always be prevented from overheating and, hence, thermal monitoring is indispensable. Since only the surface temperature of the battery can be measured, a ...
Abstract: In high-voltage dc-dc applications, the switches in the conventional two-level dual active bridge (DAB) dc-dc converter have to bear the whole port voltage, so high voltage switches should ...
Abstract: This paper evaluates the microstructure and properties of polypropylene/polyolefin elastomer (PP/POE) blends for potential recyclable HVDC cable insulation ...
Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...
We report GaN p-n diodes on free-standing GaN substrates: a record high Baliga's figure-of-merit (V<;sub>B<;/sub><;sup>2<;/sup>/ Ron) of ...
Abstract: Precipitation nowcasting is a challenging task in the context of global climate variability. However, existing radar echo or numerical weather prediction data methods lack deep modeling ...
Abstract: This amendment to IEEE Std 802.3-202x adds Clause 161 through Clause 163, Annex 120F, Annex 120G, and Annex 162A through Annex 162D, Annex 163A, and Annex 163B. This amendment includes ...
Abstract: Deep multi-modal clustering (DMC) expects to improve clustering performance by exploiting abundant information available from multiple modalities. However, different modalities usually have ...
Abstract: This paper presents ORB-SLAM, a feature-based monocular simultaneous localization and mapping (SLAM) system that operates in real time, in small and large indoor and outdoor environments.
Abstract: Convolutional Neural Networks (CNN) and Graph Neural Networks (GNN), such as Graph Attention Networks (GAT), are two classic neural network models, which are applied to the processing of ...