In most domains anomaly detection is typically cast as an unsupervised learning problem because of the infeasability of labelling large datasets. In this setup, the evaluation and comparison of different anomaly detection ...

RxJS is a popular JavaScript library for reactive programming in Web applications. It provides numerous operators to create, combine, transform, and filter discrete events and to handle errors. These operators may be ...

The increasing number of powered wheelchair users, driven by an aging global population and advancements in medical care, highlights a critical need to understand their unique experiences and challenges, particularly ...

Image restoration is essential for enhancing the quality and utility of degraded images in various applications such as autonomous driving and robotics. Traditional convolutional neural network (CNN) approaches, while ...

Falls represent a significant public health concern, particularly among older adults, with approximately 35.6 million cases annually in the United States alone. Traditional machine learning-based fall risk prediction methods ...

Classical neural network (NN) compression methods, such as NN pruning and distillation, focus on reducing the NN size. However, these methods often sacrifice accuracy in the process. To address this issue, we propose a ...

Distributed AI infrastructures are extensively employed in cloud industry settings to accommodate the growing demands of AI services. However, extending such infrastructures to the edge remains under exploration. This study ...

Image-based neural networks are widely used across diverse applications, yet their inherent susceptibility to backdoor attacks has raised growing concerns. In particular, data-free backdoor attacks, which exploit benign ...