Publications associées à How is the Weather: Automatic Inference from Images

Aggregating Spatial and Photometric Context for Photometric Stereo

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 ...

EPFL2024

Turbulence and Heat exchange in the Near-Surface Boundary Layer over Patchy Snow

Michael Haugeneder

The atmospheric layer adjacent to the earth's surface is of crucial importance for weather models due to the exchange of energy between the surface and the atmosphere. This exchange is dependent on the various surface properties and influences the state of ...

EPFL2024

Network time series forecasting in photovoltaics power production

Jelena Simeunovic

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 ...

EPFL2024

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evann Pierre Guy Courdier

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

EPFL2024

A seasonal snowpack model forced with dynamically downscaled forcing data resolves hydrologically relevant accumulation patterns

Michael Lehning, Tobias Jonas, Dylan Stewart Reynolds

The Mountain snowpack stores months of winter precipitation at high elevations, supplying snowmelt to lowland areas in drier seasons for agriculture and human consumption worldwide. Accurate seasonal predictions of the snowpack are thus of great importance ...

Frontiers Media Sa2024

Good enough: Intermediate complexity atmospheric models improve the representation of processes affecting seasonal snow

Dylan Stewart Reynolds

Snow plays a crucial role in processes regulating ecosystems, the climate, and human development. Mountain snowpack in particular has great relevance for downstream communities. Knowledge about the distribution and properties of the snowpack thus help in p ...

EPFL2024

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

Devis Tuia, Thiên-Anh Claris Nguyen, Marc Conrad Russwurm, Gaston Jean Lenczner

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Elsevier Science Inc2024

The multimodality cell segmentation challenge: toward universal solutions

Xin Yang, Bo Wang, Yixin Wang, Jun Ma, Lin Han, Maxime Emmanuel Scheder, Marco Labagnara, Sahand Jamal Rahi, Vojislav Gligorovski, Yao Zhang

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

Nature Portfolio2024

Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"

Alexis Berne, Satoshi Takahama, Athanasios Nenes, Georgia Sotiropoulou, Anne-Claire Marie Billault--Roux, Paraskevi Georgakaki, Romanos Foskinis, Kunfeng Gao

This repository contains field observations and processed data from the Weather Research and Forecasting (WRF) model simulations and the Cloud Resolving Model Radar Simulator (CR-SIM), alongside scripts designed to reproduce the figures presented in the pa ...

Zenodo2024

Incorporating Projective Geometry into Deep Learning

Michal Jan Tyszkiewicz

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

EPFL2024

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Martin Weigert

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Nature Portfolio2024

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Veronica Lily Ravano

Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

EPFL2024

Challenges of COVID-19 Case Forecasting in the US, 2020-2021

Joseph Chadi Benoit Lemaitre, Pan Xu, Myungjin Kim, Shan Yu, Lei Gao, Weitong Zhang, Wei Cao, Xinyi Li

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and ...

Public Library Science2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Towards Trustworthy Deep Learning for Image Reconstruction

Alexis Marie Frederic Goujon

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

EPFL2024

Data and scripts for the RaFSIP scheme

Athanasios Nenes, Paraskevi Georgakaki

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Zenodo2024

Machine Learning for Modeling Stock Returns

Teng Andrea Xu

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

EPFL2024

Multimodal fusion of liquid biopsy and CT enhances differential diagnosis of early-stage lung adenocarcinoma

Jun Lu, Hua Zhong, Li Zhang, Yunhua Zhang, Jiancheng Yang

This research explores the potential of multimodal fusion for the differential diagnosis of early-stage lung adenocarcinoma (LUAD) (tumor sizes < 2 cm). It combines liquid biopsy biomarkers, specifically extracellular vesicle long RNA (evlRNA) and the comp ...

Nature Portfolio2024

Urban boundary-layer flows in complex terrain: Dynamic interactions during a hot and dry summer season in Phoenix, Arizona

Aldo Brandi

Anthropogenic modification of natural landscapes to urban environments impacts land-atmosphere interactions in the boundary layer. Ample research has demonstrated the effect of such landscape transitions on development of the urban heat island (UHI), but c ...

Wiley2024

Weather Impacts on Indoor Radon Short-Term Measurements in Switzerland

Joan Rey

Radon is a natural and radioactively well-known carcinogenic indoor air pollutant. Since 2020, a radon short-term proactive methodology has been proposed by Swiss authorities, which aims to evaluate the probability of overpassing the national reference val ...

MDPI2023