Abstract: In high-speed railway (HSR) OFDM systems, achieving better channel capacity requires appropriate power allocation based on accurate channel state information (CSI). While existing deep ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...

A 27-year-old man faces capital murder charges after a double stabbing during a fight early Saturday morning near downtown Dallas. Two victims, ages 28 and 30, died at a Dallas hospital from their ...

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Abstract: In millimeter-wave (mmWave) communication systems, conventional channel estimation methods suffer from limited angle quantization resolution, leading to off-grid problems that degrade ...

When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.