Publications associées à LABORATORY EXPERIMENTS OF PULSED SUBAQEOUS SEDIMENT DENSITY FLOWS: INTERNAL STRATIFICATION AND LAYERING

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Aude Billard, Nadia Barbara Figueroa Fernandez, Mikhail Koptev

Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is construc ...

Sage Publications Ltd2024

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

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

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

Improved marine debris detection in satellite imagery with automatic refinement of coarse hand annotations

Devis Tuia, Marc Conrad Russwurm, Elif Dilge Gül

Plastic litter is a major environmental hazard that endangers human, animal, and plant health on the planet. A substantial portion of plastic pollutants is washed from rivers and beaches into the oceans and aggregates at the surface as marine debris before ...

2023

Large-scale detection of marine debris in coastal areas with Sentinel-2

Devis Tuia, Marc Conrad Russwurm

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Here, remote sensing can provide reliable estimates of plastic pollution by regularly monitoring and d ...

2023

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Seyedbehzad Bozorgtabar, Devavrat Tomar

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

IEEE2023

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

Why is the winner the best?

Adrien Raphaël Depeursinge, Jian Wang, Ho Ling Li, Gabriel Girard, Yong Yang, Fan Xia, Xiao Wang, Hui Wang, Jing Li

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really gener ...

Ieee Computer Soc2023

Tensile and creep-rupture response of additively manufactured nickel-based superalloy CM247LC

Christian Leinenbach, Rafal Wróbel

Tensile and creep rupture properties of crack-free CM247LC alloy, processed via laser powder bed fusion, have been characterised in this work at temperatures up to 1000 & DEG;C. The subject alloy matches or even exceeds the tensile performance of its direc ...

ELSEVIER2023

Influence of pore-scale heterogeneity on the precipitation patterns in Microbially Induced Calcite Precipitation (MICP)

Ariadni Elmaloglou

The principle of tailoring material properties to improve the mechanical behaviour of soils through compaction or cement grouting dates to the 60s. The increasing trends of urbanization worldwide require new solutions for the development of resilient and s ...

EPFL2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Colin Neil Jones, Melanie Nicole Zeilinger, Xuan Truong Nghiem, Roland Schwan

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

IEEE2023

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

Touradj Ebrahimi

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 ...

IEEE COMPUTER SOC2023

Quantified Effects of Multiple Parameters on Inputs and Potential Sources of Microplastics from a Typical River Flowing into the Sea

Florian Frédéric Vincent Breider, Wenxin Liu, Yang Liu

As an important connection of terrestrial and marine ecosystems, rivers input multitudinous (micro)plastics into the oceans. However, comparisons of field and estimated riverine inputs of (micro)plastics and contributions of multiple parameters are limited ...

2022

Determining crack kinematics from imaged crack patterns

Katrin Beyer, Amir Rezaie, Bryan German Pantoja Rosero, Ketson Roberto Maximiano Dos Santos

Determining the relationship between the cause of damage and the subsequent structural behavior of infrastructure systems requires an accurate characterization of the propagation of cracks, which represents the evolution of the damage state. When no inform ...

2022

Unconfined Plunging of a Hyperpycnal River Plume Over a Sloping Bed and Its Lateral Spreading: Laboratory Experiments and Numerical Modeling

Ulrich Lemmin, Koen Blanckaert, David Andrew Barry, Haoran Shi

Hyperpycnal (negatively buoyant) river inflow into lakes and oceans often develops three-dimensional (3D) plunging flow patterns when laterally unconfined. To determine the 3D flow pattern characteristics, laboratory experiments of laterally unconfined plu ...

American Geophysical Union2022

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

Giovanni De Cesare, Christian Mörtl

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. ...

International Association for Hydro-Environment Engineering and Research (IAHR)2022

3D printing of elastomeric mechanical sensors designed for human motion monitoring

Ryan Mitchell van Dommelen

In this thesis several advances are made to the emerging field of 3D printed mechanical sensors. Techniques and processes were developed to enable the integration of highly conductive, and capacitive and piezoresistive sensing features embedded within 3D p ...

EPFL2022

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

A life cycle analysis of novel lightweight composite processes: Reducing the environmental footprint of automotive structures

Véronique Michaud, Colin Gomez, Baris Çaglar, Vincent Werlen, Christian Rytka

In this study, three novel thermoplastic impregnation processes were analyzed towards automotive applications. The first process is thermoplastic compression resin transfer molding in which a glass fiber mat is impregnated in through thickness by a thermop ...

ELSEVIER SCI LTD2022

Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer

Marc Conrad Russwurm

Data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGr ...

SPRINGER INTERNATIONAL PUBLISHING AG2022