A Human-Centric Approach to Explainable AI for Personalized Education

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Now is an exciting time for the domain of Earth observation (EO), with a multitude of diverse sensors looking at the planet from satellites, airplanes or drones. The volume of imagery acquired is massive, and hold great potential for a variety of applicati ...

This article introduces a competency-based model for generative artificial intelligence (AI) literacy covering essential skills and knowledge areas necessary to interact with generative AI. The competencies range from foundational AI literacy to prompt eng ...

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

Predicting human trajectories is essential for the safe operation of autonomous vehicles, yet current data-driven models often lack robustness in case of noisy inputs such as adversarial examples or imperfect observations. Although some trajectory predicti ...

Blindness remains one of the most impairing disabilities worldwide, profoundly affecting independence, social participation, and quality of life. While assistive technologies offer partial support, they do not restore visual function. Retinal prostheses re ...

Explainable Artificial Intelligence (XAI) seeks to render Artificial Intelligence (AI) models transparent and comprehensible, potentially increasing trust and confidence in AI recommendations. This research explores the realm of XAI within unsupervised edu ...

Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an AI virtual cell (AIVC), a multi-scal ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

Earth observation (EO) is increasingly used for mapping and monitoring processes occurring at the surface of Earth. Data acquired by satellites nowadays allow us to have a global view, consistent in time, of the state of our forests, oceans, and growing ur ...

Recent years have seen remarkable advancements in saliency estimation methods, mainly due to deep learning models leveraging the widespread availability of real-world images. However, saliency is profoundly shaped by the intricacies of the human visual att ...

Deploying compute-intensive deep neural networks (DNNs) on resource-constrained end devices has become a prominent trend, enabling localized intelligence. However, efficiently deploying these DNNs at scale poses challenges. To address this, extensive resea ...

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional c ...

Architecture operates as an evolving interface that organises energy flows and stabilises material forms. It shapes the built environment by merging form with energy, creating spaces that resonate with occupants through sensory experiences, and by establis ...

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and ...

A Human-Centric Approach to Explainable AI for Personalized Education

Chat with Graph Search

Interact with Earth Observation Images using AI: Transparent Methods and Evaluation for Visual Question Answering

Generative AI Literacy: Twelve Defining Competencies

Improving the accuracy and interpretability of neural networks for wind power forecasting

Certified Human Trajectory Prediction

Using Virtual Reality to Improve Prosthetic Vision in Daily Life

Explainable AI for Unsupervised Machine Learning: A Proposed Scheme Applied to a Case Study with Science Teachers

How to build the virtual cell with artificial intelligence: Priorities and opportunities

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward

Visual Saliency Prediction for Natural Images, Comics Panels, and Comics Pages

RAPNet: Resolution-Adaptive and Predictive Early Exit Network for Efficient Image Recognition

AngioPy segmentation: An open-source, user-guided deep learning tool for coronary artery segmentation

Intensive Extensive: Merging Generative and Analytical Methods in Environmental Design Workflows

Euclid: Improving the efficiency of weak lensing shear bias calibration