Publications associées à Automated Digital Image Processing for Volume Change Measurement in Triaxial Cells

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

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

Design and Evaluation of Modular Gas and Wind Sensing Nodes for Static and Mobile Deployments

Alcherio Martinoli, Emmanuel Droz, Wanting Jin

Static and mobile sensor nodes can be employed in gas monitoring tasks to detect gas leaks in an early stage and localize gas sources. Due to the intermittent nature of gas plumes and the slow dynamics of commonly used gas sensors, measuring gas concentrat ...

2024

Setting priorities in CNF particle size measurement: What is needed vs. what is feasible

Tiffany Abitbol

Measuring the size of cellulose nanomaterials can be challenging, especially in the case of branched and entangled cellulose nanofibrils (CNFs). The International Organization for Standardization, Technical Committee 6, Task Group 1-Cellulosic Nanomaterial ...

TECH ASSOC PULP PAPER IND INC2023

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Claudio Bruschini, Edoardo Charbon, Andrei Ardelean, Mohit Gupta

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

Ieee Computer Soc2023

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Gulnaz Ganeeva

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

EPFL2023

A Cryo-CMOS Oscillator With an Automatic Common-Mode Resonance Calibration for Quantum Computing Applications

Edoardo Charbon, Fabio Sebastiano, Yue Chen

This article presents a 4-to-5 GHz LC oscillator operating at 4.2K for quantum computing applications. The phase noise (PN) specification of the oscillator is derived based on the control fidelity for a single-qubit operation. To reveal the substantial gap ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Creating and controlling exceptional points of non-Hermitian Hamiltonians via homodyne Lindbladian invariance

Fabrizio Minganti

The exceptional points (EPs) of non-Hermitian Hamiltonians (NHHs) are spectral degeneracies associated with coalescing eigenvalues and eigenvectors, which are associated with remarkable dynamical properties. These EPs can be generated experimentally in ope ...

AMER PHYSICAL SOC2022

Assessment of the Bundle SNSPD Plus FPGA-Based TDC for High-Performance Time Measurements

Christophe Marcel Georges Galland, Andrea Costa, Santiago Tarrago Velez

Counting single photons and measuring their arrival time is of crucial importance for imaging and quantum applications that use single photons to outperform classical techniques. The investigation of the coincidence, i.e. correlation, between photons can b ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Improving the Training of Compact Neural Networks for Visual Recognition

Shuxuan Guo

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

EPFL2022

Cross verified independent measurements of correlated bubble property distributions as part of the scale-up of a catalytic bubbling fluidized bed reactor

Philipp Fedor Riechmann

Methanation can be applied as part of a Power-to-Gas (PtG) concept to store renewable electricity. Using a catalytic bubbling fluidized bed (BFB) methanation reactor allows a flexible and economic operation. Properties of bubbles rising through the fluidiz ...

EPFL2022

Experimental QND measurements of complementarity on two-qubit states with IonQ and IBM Q quantum computers

Christophe Marcel Georges Galland, Nicolas Schwaller, Valeria Vento

We report the experimental nondemolition measurement of coherence, predictability and concurrence on a system of two qubits. The quantum circuits proposed by De Melo et al. (Phys Rev Lett 98(25):250501, 2007) are implemented on IBM Q (superconducting circu ...

SPRINGER2022

Natural-Looking Adversarial Examples From Freehand Sketches

Davide Nanni, Hakgu Kim

Deep neural networks (DNNs) have achieved great success in image classification and recognition compared to previous methods. However, recent works have reported that DNNs are very vulnerable to adversarial examples that are intentionally generated to misl ...

IEEE2022

Identification of optimal measurement points for energy monitoring of industrial processes: The case of milk powder production

Tuong-Van Nguyen

Meaningful energy analysis of industrial processes requires the installation of energy monitoring systems. However, a lack of systematic methods for identifying the required measurement points, joint to scarce information on the related benefits, results i ...

ELSEVIER SCI LTD2021

A Comparison of optimal measurement-system design with engineering judgement for bridge load testing

Ian Smith, Numa Joy Bertola

Due to conservative approaches in construction design and practice, infrastructure often has hidden reserve capacity. When quantified, this reserve has potential to improve decisions related to asset management. Field measurements, collected through load t ...

2021

Measurement of the CKM angle gamma and Bs0-Bs0 mixing frequency with Bs0 -> Ds -/+h +/-pi +/-pi-/+ decays

Christoph Frei, Peter Clarke, Aurelio Bay, Minh Tâm Tran, Marc-Olivier Bettler, François Fleuret, Tatsuya Nakada, Guido Haefeli, Niko Neufeld, Olivier Schneider, Hans Dijkstra, Frédéric Teubert, Gerhard Raven, Mingkui Wang, Chitsanu Khurewathanakul, Frédéric Blanc, Matthew Needham, Axel Kuonen, Olivier Göran Girard, Liang Sun, Maxime Schubiger, Brice Emile Maurin, Thibaud Humair, Hang Yin, Xiaoxue Han, Greig Alan Cowan, Paolo Durante, Jessica Prisciandaro, Guillaume Max Pietrzyk, Matthieu Philippe Luther Marinangeli, Vladislav Balagura, Lino Ferreira Lopes, Zhirui Xu, Mark Tobin, Victor Coco, Violaine Bellée, Mirco Dorigo, Yu Zheng, Vincenzo Battista, Maurizio Martinelli, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals

Pascal Fua, Pavan P Ramdya, Helge Jochen Rhodin, Semih Günel, Victor Lobato Rios, Daniel Eduardo Morales Garza, Marco Pietro Abrate, Adám Gosztolai

LiftPose3D infers three-dimensional poses from two-dimensional data or from limited three-dimensional data. The approach is illustrated for videos of behaving Drosophila, mice, rats and macaques. ...

NATURE PORTFOLIO2021

MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients

Jean-Philippe Thiran, Meritxell Bach Cuadra, Cristina Granziera, Thomas Yu, Francesco La Rosa

Background and objective: Compared to the conventional magnetization-prepared rapid gradient-echo imaging (MPRAGE) MRI sequence, the specialized magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE) shows a higher brain tissue and lesion con ...

2021

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Dario Floreano, Giuseppe Loianno, Maxim Pavliv, Fabrizio Schiano

We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector o ...

2021

Development and evaluation of galaxy shape measurement algorithms for radio interferometric data

Vasileios Angelopoulos

The purpose of this Thesis is to develop, test, and characterize different models attempting to tackle the problem of measurement of galaxy shapes applied in interferometric observations. Shape measurement is a tool for estimating the underlying shear due ...

EPFL2021