Publications related to Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

Deep Learning Theory Through the Lens of Diagonal Linear Networks

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Compact and effective photon-resolved image scanning microscope

Giorgio Tortarolo

Fluorescence confocal laser-scanning microscopy (LSM) is one of the most popular tools for life science research. This popularity is expected to grow thanks to single-photon array detectors tailored for LSM. These detectors offer unique single-photon spati ...

Spie-Soc Photo-Optical Instrumentation Engineers2024

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

Computational drug development for membrane protein targets

Pierre Vogel, Henning Paul-Julius Stahlberg, Dongchun Ni, Babatunde Edukpe Ekundayo, Shuguang Yuan

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

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Text-to-Microstructure Generation Using Generative Deep Learning

Jamie Paik

Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although rec ...

Wiley-V C H Verlag Gmbh2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Meta-learning to address diverse Earth observation problems across resolutions

Devis Tuia, Benjamin Alexander Kellenberger, Marc Conrad Russwurm

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

London2024

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

David Atienza Alonso, José Angel Miranda Calero, Jonathan Dan, Christodoulos Kechris

Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they often un ...

2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Paul Mos, Yang Lin

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

Berlin2024

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (1/6)

Jean-Philippe Thiran

This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

Zenodo2024

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

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Deep Learning Theory Through the Lens of Diagonal Linear Networks

Compact and effective photon-resolved image scanning microscope

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Computational drug development for membrane protein targets

Text-to-Microstructure Generation Using Generative Deep Learning

Random matrix methods for high-dimensional machine learning models

Meta-learning to address diverse Earth observation problems across resolutions

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (1/6)

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Compact and effective photon-resolved image scanning microscope

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Computational drug development for membrane protein targets

Text-to-Microstructure Generation Using Generative Deep Learning

Random matrix methods for high-dimensional machine learning models

Meta-learning to address diverse Earth observation problems across resolutions

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (1/6)