Taking an interdisciplinary approach to surveying issues around gender bias in textual and visual AI, we present literature on gender bias detection and mitigation in NLP, CV, as well as combined visual-linguistic models. We identify conceptual parallels ...

The integration of emotion recognition capabilities within musical instruments can spur the emergence of novel art formats and services for musicians. This paper proposes the concept of emotionally-aware smart musical instruments, a class of ...

• The new class of emotionally-aware smart musical instruments is presented
• An embedded AI agent recognizes the emotion contained in the musical signal.
• An emotionally-aware smart piano and an smart electric guitar were created.
• ...

Image analysis is a key tool for describing the detailed mechanisms of folliculogenesis, such as evaluating the quantity of mouse Primordial ovarian Follicles (PMF) in the ovarian reserve. The development of high-resolution virtual slide scanners ...

Supervised learning has become the dominant paradigm in computer-aided diagnosis. Generally, these methods assume that the training labels represent “ground truth” information about the target phenomena. In actuality, the labels, often derived ...

As deep neural networks (DNNs) are increasingly used in safety-critical applications, there is a growing concern for their reliability. Even highly trained, high-performant networks are not 100% accurate. However, it is very difficult to predict their ...

Despite the potential benefits of Artificial Intelligence (AI) to enhance public services, the implementation of AI in the public sector is still limited. In this work, we review the trustworthy AI literature in the public sector and provide ...

When AI interacts with humans in complex environments, such as aerospace manufacturing, safety of operation is of paramount importance. Trustworthiness of AI needs to be ensured through, among other things, explainability of its behaviour and ...

The notion of trustworthiness, central to many fields of human inquiry, has recently attracted the attention of various researchers in logic, computer science, and artificial intelligence (AI). Both conceptual and formal approaches for modeling ...

In smart cities, graph embedding technologies, Graph Neural Networks (GNNs), and related variants are extensively employed to address predictive tasks within complex urban networks, such as traffic management, the Internet of Things (IoT), and public ...

In the last decade, there has been a dramatic rise in phishing emails including business email compromise, and extortion attacks. Ransomware and blackmail are examples of extortion threats, where attackers force victims to follow orders, send ...$\mathrm{}$$\mathrm{}$

Contract automation is a challenging topic within Artificial Intelligence and LegalTech. From digitised contracts via smart contracts, we are heading towards Intelligent Contracts (iContracts). We will address the main challenge of iContracts: the ...

This paper delves into the verification of Convolutional Neural Networks for the crucial task of identifying vehicles in automotive images. Given the complexity and verifiability challenges of traditional object detection models, we propose a “...

In recent years, the application of artificial intelligence and machine learning techniques has gained significant traction in addressing various challenges across industries. Among these, anomaly detection has emerged as a crucial task for ...

As automatic decision-making systems advance and are deployed in many high-stake areas, ensuring fairness is becoming crucial. Although many fairness-aware algorithms have been proposed, most of them assume sufficient sensitive labels are ...

Societal acceptance and successful adoption of artificial intelligence (AI) hinge critically on our trust in AI technology. Trust becomes particularly crucial in human-AI interaction due to perceived risks arising from AI behaviors’ complexity and ...

From the innovation, Artificial Intelligence (AI) materialized as one of the noticeable research areas in various technologies and has almost expanded into every aspect of modern human life. However, nowadays, the development of AI is unpredictable with ...

Time series classification is a task which deals with temporal sequences, a prevalent data type common in domains such as human activity recognition, sports analytics and general sensing. In this area, interest in explanability has been growing as ...

Recently, there has been growing attention on behalf of both academic and practice communities towards the ability of Artificial Intelligence (AI) systems to operate responsibly and ethically. As a result, a plethora of frameworks and guidelines have ...

Predictive analytics technologies like machine learning, AI and Generative AI models like Large Language Models (LLMs), have garnered enthusiasm for their potential to improve healthcare services in smart cities. However, these rapidly developing ...

How governments, practitioners, and researchers define artificial intelligence (AI) ethics significantly impacts the AI models and systems designed and deployed. Thus, the convergence of policy goals and technical approaches is necessary for ...