Publications related to Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings

Related publications (42)

Capturing behavioral and neural variability in multi-area spiking neuronal network models

How does the brain generate behavioral responses from sensory stimuli? This sensor-to-motor transformation is a fundamental question in systems neuroscience. While recent experiments have highlighted the complexity of neural representations across the cere ...

EPFL2025

Parametrizations of all stable closed-loop responses: From theory to neural network control design

Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti

The complexity of modern control systems necessitates architectures that achieve high performance while ensuring robust stability, particularly for nonlinear systems. In this work, we tackle the challenge of designing output-feedback controllers to boost t ...

2025

Topological data analysis-based damage indices for plastered stone masonry walls under cyclic loading

Katrin Beyer

The qualitative aspect of visual inspection of damaged structures can be largely benefited by incorporating quantitative metrics. Moreover, automating this process requires the development of effective computational tools capable of making reliable assessm ...

2025

Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting

Alexandre Massoud Alahi, Kaouther Messaoud Ben Amor

Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like complex architectures customized for a specific dataset and inefficient multimoda ...

Institute of Electrical Engineering2025

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

Accelerating Transfer Learning with Near-Data Computation on Cloud Object Stores

Rachid Guerraoui, Arsany Hany Abdelmessih Guirguis, Diana Andreea Petrescu

Storage disaggregation underlies today's cloud and is naturally complemented by pushing down some computation to storage, thus mitigating the potential network bottleneck between the storage and compute tiers. We show how ML training benefits from storage ...

Association for Computing Machinery, Inc2024

SIMBa: System Identification Methods Leveraging Backpropagation

Colin Neil Jones, Giancarlo Ferrari Trecate, Muhammad Zakwan, Loris Di Natale

This manuscript details and extends the system identification methods leveraging the backpropagation (SIMBa) toolbox presented in previous work, which uses well-established machine learning tools for discrete-time linear multistep-ahead state-space system ...

2024

Drone‐Based Solar Cell Inspection With Autonomous Deep Learning

Mirko Kovac

Regular inspection and maintenance are crucial for ensuring the optimal performance of solar panels. However, conventional manual methods can be laborious, time consuming, and expensive, especially for large and inaccessible installations. Aerial inspectio ...

Wiley2024

InNeRF360: Text-Guided 3D-Consistent Object Inpainting on 360° Neural Radiance Fields

Sabine Süsstrunk, Tong Zhang, Dongqing Wang

We propose InNeRF360, an automatic system that accurately removes text-specified objects from 360 • Neural Radiance Fields (NeRF). The challenge is to effectively remove objects while inpainting perceptually consistent content for the missing regions, whic ...

IEEE2024

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

Devis Tuia, Marc Conrad Russwurm, Thiên-Anh Claris Nguyen, 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

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

Amirhossein Shahbazinia, David Atienza Alonso, Giovanni Ansaloni, Flavio Ponzina, José Angel Miranda Calero, Jonathan Dan

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

IEEE2024

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

Alberto Antonietti, Davide Bella, Pranav Rai, Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Michael Reimann, Marwan Muhammad Ahmed Abdellah, Werner Alfons Hilda Van Geit, Lida Kanari, Srikanth Ramaswamy, James Gonzalo King, Alexis Arnaudon, Ying Shi, András Ecker, Jean-Denis Georges Emile Courcol, Armando Romani, Pramod Shivaji Kumbhar, Judit Planas Carbonell, Michael Emiel Gevaert, Nadir Roman Guerrero, Liesbeth Maria L Vanherpe, Huanxiang Lu, Mohameth François Sy, Cristina Colangelo, Juan Bautista Hernando Vieites, Cyrille Pierre Henri Favreau, Genrich Ivaska, Anna-Kristin Kaufmann, Joni Henrikki Herttuainen, Elvis Boci, Vishal Sood, Thomas Brice Delemontex, Fabien Petitjean, Julian Martin Budd, Mustafa Kerem Kurban

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

2024

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

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024