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Artificial intelligence (AI) is increasingly used in an ever larger number of industries. Alongside this development, however, abundant works argue that AI-driven systems are lacking in terms of safety, ethics and transparency. As a direct consequence, the ...

The advancement of motor augmentation and the broader domain of human-machine interaction rely on a seamless integration with users' physical and cognitive capabilities. These considerations may markedly fluctuate among individuals on the basis of their ag ...

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

Deep learning models for learning analytics have become increasingly popular over the last few years; however, these approaches are still not widely adopted in real-world settings, likely due to a lack of trust and transparency. In this paper, we tackle th ...

In the context of automatic visual inspection of infrastructures by drones, Deep Learning (DL) models are used to automatically process images for fault diagnostics. While explainable Artificial Intelligence (AI) algorithms can provide explanations to asse ...

As the field of ethology advances, especially over the past two decades, the role of animal-robot interaction tools has increasingly become essential. This importance arises from the need for controlled, repetitive, repeatable, and long-duration experiment ...

Recent works have identified a gap between research and practice in artificial intelligence security: threats studied in academia do not always reflect the practical use and security risks of AI. For example, while models are often studied in isolation, th ...

The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain- ...

The past few decades have seen important efforts to introduce more ethics into engineering education programs around the world, while adapting to the evolution of ethical concerns, notably in relation to digital technology and artificial intelligence. Even ...

Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered a ...

Nowadays, search engines, social media or news aggregators are the preferred services for news access. Aggregation is mostly based on artificial intelligence technologies raising a new challenge: Trust has been ranked as the most important factor for media ...

DNA-based nanostructures are actively gaining interest as tools for biomedical and therapeutic applications following the recent development of protective coating strategies prolonging structural integrity in physiological conditions. For tailored biologic ...

This paper describes SciClops, a method to help combat online scientific misinformation. Although automated fact-checking methods have gained significant attention recently, they require pre-existing ground-truth evidence, which, in the scientific context, ...

The conversion of sugarcane, the world's largest crop, to energy vectors, namely first and second-generation ethanol and electricity, is an ongoing scientific endeavor. This conversion makes use of complex processes with numerous unit operations and proces ...

In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles in peer-reviewed journals. One challenge for modern neuroinformatics is to design methods to make the knowledge from the tremend ...

Computational models of biological systems aim at accurately simulating in vivo phenomena. They have become a very powerful tool enabling scientists to study complex behavior. A side effect of their success Unfortunately exists and is observed as an increa ...

Visualbiotech

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Voices from the Frontline: Revealing the AI Practitioners' viewpoint on the European AI Act

Evaluating initial usability of a hand augmentation device across a large and diverse sample

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations

Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design

Exploiting Explanations to Detect Misclassifications of Deep Learning Models in Power Grid Visual Inspection

Challenges and approaches in bridging the biomimicry gap in biohybrid systems of fish and robots

Towards more Practical Threat Models in Artificial Intelligence Security

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain

A Game-Based Approach to Develop Engineering Students’ Awareness About Artificial Intelligence Ethical Challenges

Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences

Trust Indicators and Explainable AI: A Study on User Perceptions

Quantification of Strand Accessibility in Biostable DNA Origami with Single-Staple Resolution

SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking

Review of design works for the conversion of sugarcane to first and second-generation ethanol and electricity

Agile in-litero experiments : how can semi-automated information extraction from neuroscientific literature help neuroscience model building?

Towards a Scientific Model Management System