Abstract: Low-latency communication plays an increasingly important role in delay-sensitive applications by ensuring the real-time information exchange. However, due to the constraint on the maximum ...

Abstract: Predicting the plausible future paths of pedestrians is essential for human-involved applications (e.g., autonomous driving and service robotics). Existing pedestrian trajectory prediction ...

Abstract: The thriving domain of the Internet of Bio-Nano Things (IoBNT) promises revolutionary advances in biomedicine, enabling biosensing, health monitoring, and therapeutic capabilities at the ...

Abstract: Methods for joint classification of hyperspectral images (HSIs) with high dimensionality and spectral correlation and other sensor data (e.g., optical, infrared, radar, etc.) are important ...

Abstract: Accurately predicting the long-term demand for public bicycle systems (PBS) is crucial for policy implementations such as operator rebalancing. With the continuous advancement of deep ...

Abstract: The rise of synthetic speech technologies has triggered growing concerns about the increasing difficulty in distinguishing between real and fake voices. In this context, we propose novel ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=7727 ...

Abstract: Passive indoor localization is emerging as a transformative technology in consumer electronics, notably improving applications in smart buildings, indoor navigation, and dynamic beamforming.

Abstract: In the 6G integrated air-ground network, the process of accomplishing complex tasks through the integrated multimodal communication faces challenges induced by unmanned aerial vehicles (UAVs ...

Abstract: Dark soliton microcombs with a high repetition rate and high line power can be generated in a nonlinear ring with normal group velocity dispersion (GVD), making them suitable for various ...

Abstract: U-shaped encoder-decoder models have excelled in automatic medical image segmentation due to their hierarchical feature learning capabilities, robustness, and upgradability. Purely CNN-based ...

Abstract: 3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception. However, current 3D trackers face issues with ...