Space Odyssey - Efficient Exploration of Scientific Data

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Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

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 ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

The diffusion of energy technologies is key for supporting the energy transition. While social influence and peer effects have been extensively studied on the demand side and found to impact adoption, less focus has been given to the role of information ne ...

Snowfall is an essential component of the hydrological cycle, as it is involved in most precipitation on Earth, either directly as snow falling to the ground or indirectly as rain melted from snow. At the same time, the ice phase of clouds and precipitatio ...

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

In this study, we present the deep learning image segmentation model for drone-based grain size analysis of gravel bars called GALET. The objectives are to quantify the performance of the code and to test its applicability in river research and management. ...

Most of the world population lives in urban areas, the share of the urban population is estimated to increase in the future decades. The complexity of different land uses and services in urban areas, which composes the built environment, influences human h ...

Maxwell's equations govern light propagation and its interaction with matter. Therefore, the solution of Maxwell's equations using computational electromagnetic simulations plays a critical role in understanding light-matter interaction and designing optic ...

Recently, it has been shown that, in spite of the significant performance of deep neural networks in different fields, those are vulnerable to adversarial examples. In this paper, we propose a gradient-based adversarial attack against transformer-based tex ...

In the last decade, deep neural networks have achieved tremendous success in many fields of machine learning. However, they are shown vulnerable against adversarial attacks: well-designed, yet imperceptible, perturbations can make the state-of-the-art deep ...

With the current exponential growth of video-based social networks, video retrieval using natural language is receiving ever-increasing attention. Most existing approaches tackle this task by extracting individual frame-level spatial features to represent ...

We address the task of automatically detecting and counting seabirds in unmanned aerial vehicle (UAV) imagery using deep convolutional neural networks (CNNs). Our study area, the coast of West Africa, harbours significant breeding colonies of terns and gul ...

Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

The integration of solar technology in the built environment is realized mainly through rooftop-installed panels. In this paper, we leverage state-of-the-art Machine Learning and computer vision techniques applied on overhead images to provide a geo-locali ...

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe ...

In this thesis, an original database is constituted, described and exploited in a geohistorical perspective, containing the registration of the population at the local level for the fifteen censuses conducted in Albania between 1918 and 2011. The precision ...

Space Odyssey - Efficient Exploration of Scientific Data

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Network time series forecasting in photovoltaics power production

Aggregating Spatial and Photometric Context for Photometric Stereo

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

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Transfer learning application of self-supervised learning in ARPES

Diffusion of energy technologies: the role and dynamics of supply-side information networks

Snowfall microphysics: a dual-frequency and Doppler spectral radar perspective

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

GALET: A deep learning image segmentation model for drone-based grain size analysis of gravel bars

Geographic clusters of objectively measured physical activity and the characteristics of their built environment in a Swiss urban area

Spatial analysis of the Healthy Built Environment: an application on Cardiovascular Risk Factors in the canton of Geneva

MaxwellNet: Physics-driven deep neural network training based on Maxwell's equations

Block-Sparse Adversarial Attack To Fool Transformer-Based Text Classifiers

Towards Verifiable, Generalizable and Efficient Robust Deep Neural Networks

Semantics-Aware Spatial-Temporal Binaries for Cross-Modal Video Retrieval

21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Quantification of the suitable rooftop area for solar panel installation from overhead imagery using Convolutional Neural Networks

Pretraining boosts out-of-domain robustness for pose estimation

Géohistoire de l'Albanie moderne. Une lecture des recensements de 1918 à 2011