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Direct Prediction of 3D Body Poses from Motion Compensated Sequences

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Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond

Reto Georg Trappitsch

Correlated errors of experimental data are a common but often neglected problem in physical sciences. Various tools are provided here for thorough propagation of uncertainties in cases of correlated errors. Discussed are techniques especially applicable to ...

ELSEVIER2023

Distribution-on-distribution regression via optimal transport maps

Victor Panaretos, Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...

OXFORD UNIV PRESS2022

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Julien Favre, Brigitte Jolles-Haeberli

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

FRONTIERS MEDIA SA2023

Feature-based no-reference video quality assessment using Extra Trees

Arash Amini, Hatef Otroshi Shahreza

With the emergence of social networks and improvements in the internet speed, the video data has become an ever-increasing portion of the global internet traffic. Besides the content, the quality of a video sequence is an important issue at the user end wh ...

WILEY2022

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Devis Tuia, Marc Conrad Russwurm, Lloyd Haydn Hughes

In this study, we examine the potential of several self-supervised deep learning models in predicting forest attributes and detecting forest changes using ESA Sentinel-1 and Sentinel-2 images. The performance of the proposed deep learning models is compare ...

The Institute of Electrical and Electronics Engineers, Inc2023

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Olga Fink, Luca Biggio

On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability impr ...

2023

Dual-Arm Control for Coordinated Fast Grabbing and Tossing of an Object

Aude Billard, Michael Bosongo Bombile

Picking up objects to toss them on a conveyor belt are activities generated on a daily basis in the industry. These tasks are still done largely by humans. This paper proposes a unified motion generator for a bimanual robotic systems that enables two 7 deg ...

2022

Encoder-Decoder Models for Human Segmentation and Motion Analysis

Isinsu Katircioglu

Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...

EPFL2022

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean

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

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - Part 2: Shine on you, crazy peroxide

César Pulgarin, Stefanos Giannakis

In this second part of the development of a mechanistic kinetic model of the solar inactivation of E. coli enhanced with hydrogen peroxide, we evaluate the mechanisms based on photonic inactivation and integrate them into the kinetic model of the dark proc ...

ELSEVIER SCIENCE SA2022

Rigidity-Aware Detection for 6D Object Pose Estimation

Mathieu Salzmann, Yinlin Hu

Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...

Ieee Computer Soc2023

Personalized predictions of adverse side effects of the COVID-19 vaccines

Nahal Mansouri, Sahand Jamal Rahi

Background: Misconceptions about adverse side effects are thought to influence public acceptance of the Coronavirus disease 2019 (COVID-19) vaccines negatively. To address such perceived disadvantages of vaccines, a novel machine learning (ML) approach was ...

ELSEVIER SCI LTD2023

Minimax rate for optimal transport regression between distributions

Victor Panaretos, Laya Ghodrati

Distribution-on-distribution regression considers the problem of formulating and es-timating a regression relationship where both covariate and response are probability distributions. The optimal transport distributional regression model postulates that th ...

ELSEVIER2022

Explanation of Optical Force and Torque on Nanomotors as the Interplay of Huygens Sources

Olivier Martin, Karim Achouri, Mintae Chung

Being able to understand how optical forces emerge from the interaction of light with matter is paramount for controlling the motion of nanoparticles as well as powering nanomotors. The purpose of this work is to uncover the physical mechanisms at the orig ...

IEEE2022

Scaling behavior of bedload transport: what if Bagnold was right?

Christophe Ancey

There is a paradox in the relationship between bedload transport rates and flow variables: laboratory and field studies have reported on how bedload transport rates depend on flow variables through a power law, but none of the empirical laws fitted to the ...

2023

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Beril Besbinar

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

EPFL2022

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

David Julian Gonon

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

EPFL2023

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

Olga Fink, Ismail Nejjar

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep feature encoder by minimizing the discrepa ...

IEEE2023

Numerical and experimental investigation of spiral-grooved gas journal bearings

Elia Iseli

Small-scale turbomachinery is increasingly used in carbon-free energy conversion systems, such as commercial or domestic scale heat pumps, fuels cells for transportation and waste heat recovery. The usage of aerodynamic bearings allows the design of compac ...

EPFL2022

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022