Learning-based surface reconstruction based on unsigned distance functio...
Surface reconstruction from raw point clouds has been studied for decade...
To improve the application-level communication performance, scheduling o...
In the field of few-shot learning (FSL), extensive research has focused ...
Implementing existing federated learning in massive Internet of Things (...
By flexibly manipulating the radio propagation environment, reconfigurab...
Over-the-air federated learning (AirFL) allows devices to train a learni...
Indoor multi-robot communications face two key challenges: one is the se...
RGB-thermal salient object detection (RGB-T SOD) aims to locate the comm...
This paper investigates the use of the reconfigurable dual-functional su...
In this letter, we study a wireless federated learning (FL) system where...
The proliferation and variety of Internet of Things devices means that t...
Healthcare data contains sensitive information, and it is challenging to...
Currently, most of the research in digital twins focuses on simulation a...
By exploiting the superiority of non-orthogonal multiple access (NOMA),
...
This paper investigates the model aggregation process in an over-the-air...
Cell-free network is considered as a promising architecture for satisfyi...
This paper investigates the problem of resource allocation for unmanned
...
In this letter, we study the secure communication problem in the unmanne...
This paper proposes a novel framework of resource allocation in multi-ce...
Endoscopic diagnosis is an important means for gastric polyp detection. ...
Matrix factorization (MF) is extensively used to mine the user preferenc...
In this paper, we propose a two-layer framework to learn the optimal han...
Real-world face detection and alignment demand an advanced discriminativ...