Publications related to Machine learning enhanced tomographic reconstruction for multispectral imaging on TCV

Related publications (18)

Fully data-driven and modular building thermal control with physically consistent modeling

Benjamin Bejar Haro, Carl Pierre Jacques Remlinger

Machine learning has experienced significant growth in the smart building sector, whether for building modeling or energy management. Data-driven approaches leverage available measurements to bypass the slow and costly calibration of physics-based models, ...

2025

Rapid prediction of phonon density of states by crystal attention graph neural network and high-throughput screening of candidate substrates for wide bandgap electronic cooling

Changpeng Lin

Machine learning has demonstrated superior performance in predicting vast materials properties. However, predicting a spectral-like continuous material property such as phonon density of states (DOS) is more challenging for machine learning. In this work, ...

2025

From Pose to Behavior: Advancing Multi-Individual Pose Estimation and Hierarchical Action Segmentation with Transformers

Lucas Maximilian Stoffl

Accurately measuring behavior is critical to understanding brain function. While traditional behavioral analysis has relied on human observation and manual processing, advances in machine learning and computer vision have begun to automate the field. This ...

EPFL2025

Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers

Olga Fink, Gaëtan Michel Frusque, Florent Evariste Forest

Commercial high-voltage circuit breaker (CB) condition monitoring systems rely on directly observable physical parameters such as gas filling pressure with pre-defined thresholds. While these parameters are crucial, they only cover a small subset of malfun ...

2025

NNG-Mix: Improving Semi-Supervised Anomaly Detection with Pseudo-Anomaly Generation

Olga Fink, Gaëtan Michel Frusque

Anomaly detection (AD) is essential in identifying rare and often critical events in complex systems, finding applications in fields such as network intrusion detection, financial fraud detection, and fault detection in infrastructure and industrial system ...

2024

Boosting Semi-supervised Crowd Counting with Scale-based Active Learning

Tong Zhang

The core of active semi-supervised crowd counting is the sample selection criteria. However, the scale factor has been neglected in active learning approaches despite the fact that the scale of heads varies drastically in the crowd images. In this paper, w ...

Association for Computing Machinery, Inc2024

Error field detection and correction studies towards ITER operation

Olivier Sauter

In magnetic fusion devices, error field (EF) sources, spurious magnetic field perturbations, need to be identified and corrected for safe and stable (disruption-free) tokamak operation. Within Work Package Tokamak Exploitation RT04, a series of studies hav ...

IOP Publishing Ltd2024

Prediction of mycotoxin response of DNA-wrapped nanotube sensor with machine learning

Ardemis Anoush Boghossian, Sara Behjati, Sayyed Hashem Sajjadi, Yahya Rabbani

DNA-wrapped single-walled carbon nanotubes (DNA-SWCNTs) have demonstrated great versatility as optical sensors. SWCNTs emit a near-infrared fluorescence that is responsive to the slightest changes in their environment, enabling the creation of sensors that ...

2023

Data analysis techniques for the visualization and classification of historical vehicle engines' health status using data-driven solutions

Alejandro Roda Buch

In the field of cultural heritage, the use of non-destructive techniques to determine the state ofconservation of an artifact is of the utmost importance, to avoid damage to the object itself. In this paper, we present a data pipeline and several machine l ...

ASSOC PROFISSIONAL CONSERVADORES-RESTAURADORES PORTUGAL2023

PET REBINNING WITH REGULARIZED DENSITY SPLINES

Michaël Unser

PET reconstruction algorithms have long relied on sinogram rebinning. However, as detectors grow smaller in a recent wave of cutting-edge scanners, individual sensors no longer accrue hundreds of photons. Instead, most detect a single photon or none at all ...

IEEE2023

Machine Learning Models for Mycobacterium tuberculosis In Vitro Activity: Prediction and Target Visualization

Anthony Vocat

Tuberculosis (TB) is a major global health challenge, with approximately 1.4 million deaths per year. There is still a need to develop novel treatments for patients infected with Mycobacterium tuberculosis (Mtb). There have been many large-scale phenotypic ...

AMER CHEMICAL SOC2022

Reviewing the application of machine learning methods to model urban form indicators in planning decision support systems : potential, issues and challenges

Jérôme Chenal, Rémi Jaligot

Modern cities dynamically face several challenges including digitalization, sustainability, resilience and economic development. Urban planners and designers must develop urban forms that address these challenges. With the integration of new communication ...

2022

Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

Patrick Hümbeli

Near-term quantum devices can be used to build quantum machine learning models, such as quantum kernel methods and quantum neural networks (QNN), to perform classification tasks. There have been many proposals on how to use variational quantum circuits as ...

2022

Global fluid simulation of plasma turbulence in a stellarator with an island divertor

Paolo Ricci, Joaquim Loizu Cisquella, Maurizio Giacomin, António João Caeiro Heitor Coelho

Results of a three-dimensional, flux-driven, electrostatic, global, two-fluid turbulence simulation for a five-field period stellarator with an island divertor are presented. The numerical simulation is carried out with the GBS code, recently extended to s ...

IOP Publishing Ltd2022

Effects of illuminance intensity on the green channel of remote photoplethysmography (rPPG) signals

Ata Jedari Golparvar

Point-of-care remote photoplethysmography (rPPG) devices that utilize low-cost RGB cameras have drawn considerable attention due to their convenience in contactless and non-invasive vital signs monitoring. In rPPG, sufficient lighting conditions are essent ...

SPRINGER2022

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on past observed trajectories and tend to fail around abrupt dynamic changes, s ...

2022

Multi-agent maintenance scheduling of generation unit in electricity market using safe deep reinforcement learning algorithm

Olga Fink

Improving maintenance scheduling of generation units in an electricity market would increase the safety and reliability of the system. This problem can be modeled as a multi-agent bi-level decision-making problem associated with some safety constraints. In ...

2022

Using wavelets to capture deviations from smoothness in galaxy-scale strong lenses

Frédéric Courbin, Georgios Vernardos, Aymeric Alexandre Galan, Austin Chandler Peel

Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens structures spanning a la ...

EDP SCIENCES S A2022