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Abstract: The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology ...

Abstract: Satellite communication offers the prospect of service continuity over uncovered and under-covered areas, service ubiquity, and service scalability. However, several challenges must first be ...

Book Abstract: "In a world of huge, interconnected networks that can be completely blacked out by disturbances, POWER SYSTEM PROTECTION offers you an improved understanding of the requirements ...

Abstract: The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Transformer ...

Abstract: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex ...

Abstract: Channel prediction is an effective approach for reducing the feedback or estimation overhead in massive multi-input multi-output (m-MIMO) systems. However, existing channel prediction ...

Abstract: The transportation department relies on accurate traffic forecasting for effective decision-making. However, determining relevant parameters for existing traffic flow prediction models poses ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=4 ...

Abstract: The rapidly growing importance of machine learning (ML) applications, coupled with their ever-increasing model size and inference energy footprint, has created a strong need for specialized ...

Abstract: Deep learning has become increasingly popular in hyperspectral image (HSI) and light detection and ranging (LiDAR) data classification, thanks to its powerful feature learning and ...