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

Parity in bacterial communities and resistomes: Microplastic and natural organic particles in the Tyrrhenian Sea

Florian Frédéric Vincent Breider, Sylvain Coudret

Petroleum-based microplastic particles (MPs) are carriers of antimicrobial resistance genes (ARGs) in aquatic environments, influencing the selection and spread of antimicrobial resistance. This research characterized MP and natural organic particle (NOP) ...

2024

Adsorption of Copper by Naturally and Artificially Aged Polystyrene Microplastics and Subsequent Release in Simulated Gastrointestinal Fluid

Florian Frédéric Vincent Breider, Thibault Béranger Masset, Lu Zhou

Microplastics, especially aged microplastics can become vectors of metals from environment to organisms with potential negative effects on food chain. However, a few studies focused on the bioavailability of adsorbed metals and most studies related to aged ...

2024

Inhalation of Microplastics—A Toxicological Complexity

Florian Frédéric Vincent Breider, Myriam Borgatta

Humans are chronically exposed to airborne microplastics (MPs) by inhalation. Various types of polymer particles have been detected in lung samples, which could pose a threat to human health. Inhalation toxicological studies are crucial for assessing the e ...

2024

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Alexander Carl Unnervik

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Devis Tuia, Thiên-Anh Claris Nguyen, Marc Conrad Russwurm, Gaston Jean Lenczner

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Elsevier Science Inc2024

Predicting the long-term collective behaviour of fish pairs with deep learning

Francesco Mondada, Alexandre Massoud Alahi, Vaios Papaspyros

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

2024

Incorporating Projective Geometry into Deep Learning

Michal Jan Tyszkiewicz

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

EPFL2024

Understanding generalization and robustness in modern deep learning

Maksym Andriushchenko

In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

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

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

Berend Smit, Sauradeep Majumdar, Xiaoqi Zhang, Hyunsoo Park

The combination of several interesting characteristics makes metal-organic frameworks (MOFs) a highly sought-after class of nanomaterials for a broad range of applications like gas storage and separation, catalysis, drug delivery, and so on. However, the e ...

Royal Soc Chemistry2024

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Ismail Nejjar, Olga Fink, Mengjie Zhao

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these ...

2024

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Seyed Mohammad Mahdi Johari

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

EPFL2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Michele Bianco, Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

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

Non-contact robotic manipulation of floating objects: exploiting emergent limit cycles

Nana Obayashi, Josephine Anna Eleanor Hughes

The study of non-contact manipulation in water, and the ability to robotically control floating objects has gained recent attention due to wide-ranging potential applications, including the analysis of plastic pollution in the oceans and the optimization o ...

Frontiers Media Sa2023

High-performance triboelectric nanogenerator via photon-generated carriers for green low-carbon system

Xin Chen

Enhancing the surface charge density and reducing the output impedance via innovative techniques are essential to accelerate the commercialization of triboelectric nanogenerators (TENGs). However, methods for increasing output performance have numerous lim ...

Elsevier2023

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

Photodegradation of biodegradable plastics in aquatic environments: Current understanding and challenges

Florian Frédéric Vincent Breider, Vinhteang Kaing

Direct photolysis and indirect photolysis are important abiotic processes in aquatic environments through which plastics can be transformed physically and chemically. Transport of biodegradable plastics in water is influenced by vertical mixing and turbule ...

2023

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations

Tanja Christina Käser Jacober, Vinitra Swamy, Jibril Albachir Frej

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

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