The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …

The high mortality rate and prevalence of cardiovascular disease (CVD) make early
detection of the disease essential. Due to its simplicity and low cost, the phonocardiogram …

Semantic segmentation technique plays a crucial role in Internet of Things applications,
such as industrial robotics and self‐driving. Recently deep learning approaches have …

Recognizing typical components of the satellite is a challenging task for on-orbit services.
This article proposes a YOLOv5-based satellite components recognition model (YSCRM) on …

With the emergence of intelligent services and applications powered by artificial intelligence
(AI), the Internet of Things (IoT) affects many aspects of our daily lives. Traditional …

Federated learning is widely used in the context of wireless networks to protect sensitive
user data. However, centralized federated learning encounters some issues when applied to …

Building detection from panchromatic (PAN) and multispectral (MS) images is an essential
task for many practical applications. In this article, a dual-stream asymmetric fusion network …

Federated learning (FL), as a machine learning framework, has garnered substantial
attention from researchers in recent years. FL makes it possible to train a global model …

Signal detection is one of the most critical and challenging issues in ambient backscatter
communication (AmBC) systems. In this paper, a multi-antenna AmBC signal detection …

Discriminative correlation filters (DCFs) have shown promising tracking performance in
recent years thanks to the powerful representation ability of deep features. However, a large …