Learning to Match Aerial Images with Deep Attentive Architectures

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Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

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Computer simulations are often used as support material for science education, as they can engage students through inquiry-based learning, promote their active interaction in the experimentation phase, and help them visualize abstract concepts. For instanc ...

Learning to Match Aerial Images with Deep Attentive Architectures

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Aggregating Spatial and Photometric Context for Photometric Stereo

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Incorporating Projective Geometry into Deep Learning

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

GELEX: Generative AI-Hybrid System for Example-Based Learning

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

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Robust machine learning for neuroscientific inference

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Social Opinion Formation and Decision Making Under Communication Trends

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

How to support students to develop coaching and peer teaching skills

Optimizing Dynamic Aperture Studies with Active Learning

Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes

Enabling Uncertainty Estimation in Iterative Neural Networks

Understanding generalization and robustness in modern deep learning

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Teacher-Mediated and Student-Led Interaction with a Physics Simulation: Effects on the Learning Experience