The Skin of Venice: A Computational Approach to the City's Urban Structure

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This thesis addresses key challenges in developing adaptive lower-limb exoskeletons to enhance balance, mobility, and user autonomy during daily living activities. It presents a comprehensive exploration of three critical aspects: push recovery during stan ...

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 ...

Facial paralysis is a highly burdening condition, resulting in a patient's inability to move his musculature on one or both sides of the mouth. The restoration of facial movement is crucial for enhancing the overall patients' quality of life. The use of DE ...

As one of the major threats to women's health worldwide, breast cancer requires early diagnosis and accurate classification, since they are key to optimizing therapeutic interventions and ensuring precise prognosis. Recently, deep learning has demonstrated ...

Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

Buildings significantly impact urban energy consumption. Mobile passive solutions, such as manual solar protections, can mitigate heat gains, but their effectiveness depends on occupants’ decisions. Analyzing occupant adjustments of manual systems is chall ...

3D displays are becoming available to mainstream consumers, offering the ability to view and interact with 3D content without wearing AR/VR glasses. This paper reports the findings of a user study that compares the performance of a range of different input ...

Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the rendered images and the segmentation masks that we use to train our model on HO3Dv2 dataset. The overall str ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

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 ...

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 ...

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

Accurate real-time prediction of aerodynamic forces is crucial for the navigation of unmanned aerial vehicles (UAVs). This paper presents a data-driven aerodynamic force prediction model based on a small number of pressure sensors located on the surface of ...

The work presented in this thesis lies at the intersection of Machine Learning (ML) and control theory. The first part is dedicated to the design of Deep Neural Network (DNN) architectures with specific numerical properties, inspired by dynamical systems m ...

Cardiomyocyte alignment in myocardium tissue plays a significant role in the physiological, electrical, and mechanical functions of the myocardium. It remains, however, difficult to align cardiac cells in a 3D in vitro heart model. This paper proposes a si ...

The Skin of Venice: A Computational Approach to the City's Urban Structure

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Partial Assistance with Lower-Limb Exoskeletons to Enhance Gait and Balance in Daily Living Activities

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

DEMO: Dielectric elastomer actuators (DEAs) for the restoration of facial movements

Mspo: a Machine Learning Hyperparameter Optimization Method for Enhanced Breast Cancer Image Classification

Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology

Machine-learning to analyze human-building interactions: How do people use mobile solar protections?

Comparison of Mouse, 6DoF Controller and Pen Interactions on a Glasses-Free 3D Display

Synthetic data (Part 2) for "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields"

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

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

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

Meta-learning to address diverse Earth observation problems across resolutions

Machine-Learning-Enhanced Real-Time Aerodynamic Forces Prediction Based on Sparse Pressure Sensor Inputs

Navigating the Loop: From Control Systems to Neural Networks and Back

A Three-Dimensional Engineered Cardiac In Vitro Model: Controlled Alignment of Cardiomyocytes in 3D Microphysiological Systems