Publications associées à Image reconstruction method based on a trained non-linear mapping

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

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

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

Dense Image-based Predictions for Comics Analysis

Deblina Bhattacharjee

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

EPFL2023

Detecting Anomalies and Obstacles in Road Scenes

Krzysztof Maciej Lis

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

EPFL2023

Attribute Prediction as Multiple Instance Learning

Devis Tuia, Diego Marcos Gonzalez

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

2022

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Pascal Fua, Pamuditha Udaranga Wickramasinghe, Patrick Moller Jensen, Mian Akbar Shah

There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an approach to volume ...

Springer2022

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

Amplitude and phase reconstruction for Low-Energy Electron Holography of individual proteins

Hannah Julia Ochner

Single-molecule imaging methods are of importance in structural biology, and specifically in the imaging of proteins, since they can elucidate conformational variability and structural changes that might be lost in imaging methods relying on averaging proc ...

EPFL2022

An Open-Source Whole Slide Image Registration Workflow at Cellular Precision Using Fiji, QuPath and Elastix

Olivier Burri, Jessica Sordet, Arne Seitz, Romain Guiet, Nicolas René Chiaruttini

Image analysis workflows for Histology increasingly require the correlation and combination of measurements across several whole slide images. Indeed, for multiplexing, as well as multimodal imaging, it is indispensable that the same sample is imaged multi ...

FRONTIERS MEDIA SA2022

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

Human-Centered Scene Understanding via Crowd Counting

Weizhe Liu

Human-centered scene understanding is the process of perceiving and analysing a dynamic scene observed through a network of sensors with emphasis on human-related activities. It includes the visual perception of human-related activities from either single ...

EPFL2021

Supervised Learning With Perceptual Similarity for Multimodal Gene Expression Registration of a Mouse Brain Atlas

Henry Markram, Felix Schürmann, Csaba Erö, Daniel Keller, Huanxiang Lu, Francesco Casalegno, Dimitri Bruno Marie Rodarie

The acquisition of high quality maps of gene expression in the rodent brain is of fundamental importance to the neuroscience community. The generation of such datasets relies on registering individual gene expression images to a reference volume, a task en ...

FRONTIERS MEDIA SA2021

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

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

Image reconstruction for novel time domain near infrared optical tomography: towards clinical applications

Edoardo Charbon, Scott Anthony Lindner, Jingjing Jiang, Chunmin Zhang, Martin Wolf

Near infrared optical tomography (NIROT) is an emerging modality that enables imaging the oxygenation of tissue, which is a biomarker of tremendous clinical relevance. Measuring in reflectance is usually required when NIROT is applied in clinical scenarios ...

2020

Precision measurement of the Xi(++)(cc) mass

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, Frédéric Blanc, Matthew Needham, Olivier Göran Girard, Lesya Shchutska, Liang Sun, Maxime Schubiger, Thibaud Humair, Xiaoqing Zhou, Hang Yin, Xiaoxue Han, Luis Alberto Granado Cardoso, Paolo Durante, Guillaume Max Pietrzyk, Matthieu Philippe Luther Marinangeli, Daniel Hugo Cámpora Pérez, Vladislav Balagura, Lino Ferreira Lopes, Albert Puig Navarro, Zhirui Xu, Mark Tobin, Victor Coco, Violaine Bellée, Mirco Dorigo, Yu Zheng, Alexey Boldyrev, Simone Meloni, Maurizio Martinelli, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Improvement of Mott spin polarimeters: An overlooked redundancy

Mauro Fanciulli

In Mott polarimeters, the measurement of the spin polarization of an electron beam along two perpendicular quantization axes is commonly performed by collecting scattered electrons with four independent detectors placed azimuthally at 90 degrees from each ...

2020

ExprADA: Adversarial domain adaptation for facial expression analysis

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

2020