We address ECG data classification, using methods from explainable artificial intelligence (XAI). In particular, we focus on the extended performance of the ST-CNN-5 model compared to established mod- els. The model ...

This paper introduces a novel solution for personal recommendation in consumer electronic applications. It addresses, on the one hand, the data confidentiality during the training, by exploring federated learning and trusted ...

Advances in Deep Learning (DL), Big Data and image processing have facilitated online disinformation spreading through Deepfakes. This entails severe threats including public opinion manipulation, geopolitical tensions, ...

Artificial intelligence-based algorithms are widely adopted in critical applications such as healthcare and autonomous vehicles. Mitigating the security and privacy issues of AI models, and enhancing their trustworthiness ...

One of the most challenging problems when diagnosing autism spectrum disorder (ASD) is the need for long sets of data. Collecting data during such long periods is challenging, particularly when dealing with children. This ...

Inequality among people has several unwanted effects, in humanistic, social and economic contexts. Several studies address distributional preferences among groups, but little is known about when inequality issues are focused ...

Several studies have documented the navigation requirements and preferences of people with visual impairments. The primary methods used in such studies were interviews and surveys. With the same goal, this study employed ...

Websites are used for many different purposes and can also be designed in different ways with different styles. Certain website designs use persistent headers, while some alternatively use non-persistent headers. Online ...

Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ...

The evolution of a complex multi-state system is often interpreted as a continuous-time Markovian process. To model the relaxation dynamics of such systems, we introduce an ensemble of random sparse matrices which can be ...