Publications associées à Label-Efficient Deep Learning Methods for Event Detection, Object Segmentation and Cell Tracking in Biological Microscopy Images

Publications associées (21)

Neuroscience-inspired computer vision and language modeling for behavior analysis

Measuring animal behaviors is a crucial task in a range of scientific applications. Modern approaches with deep neural networks calls for developing solutions that solve a wide range of vision and language tasks. This ubiquitous need for understanding beha ...

EPFL2025

A gentle introduction and tutorial on Deep Generative Models in transportation research

Zhixiong Jin

Deep Generative Models (DGMs) have rapidly advanced in recent years, becoming essential tools in various fields due to their ability to learn data distributions and generate synthetic data. Their importance in transportation research is increasingly recogn ...

2025

Evaluating Language Biases in Remote Sensing Visual Question Answering: The role of spatial attributes, language diversity, and the need for clearer evaluation

Devis Tuia, Vincent Alexandre Mendez, Christel Marie Tartini-Chappuis

Remote sensing visual question answering (RSVQA) opens new opportunities for the use of Earth observation imagery by the general public, by enabling human-machine interaction with natural language. Building on the recent advances in natural language proces ...

Institute of Electrical and Electronics Engineers (IEEE)2025

Ultra small biomorphic cantilevers for high-speed atomic force microscopy

Bahareh Ghadiani

Atomic force microscopy (AFM) has long been recognized as a potent tool for capturing high-resolution topographical data across a wide spectrum of samples. However, this superior spatial imaging capability has traditionally been counterbalanced by its rela ...

EPFL2025

Ground-Truth Effects in Learning-Based Fiber Orientation Distribution Estimation in Neonatal Brains

Jean-Philippe Thiran, Meritxell Bach Cuadra, Rizhong Lin, Hamza Kebiri

Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive method for depicting brain microstructure in vivo. Fiber orientation distributions (FODs) are mathematical representations extensively used to map white matter fiber configurations. Recently, FO ...

Springer Science and Business Media Deutschland GmbH2025

One-Pass Generation of Multivariate Time Series through Conditional Multivariate Modeling

Florent Evariste Forest

In recent years, exploring deep generative models for generating time series has garnered significant interest within the research community. These models have found wide-ranging applications in areas such as data augmentation, scenario simulation, and the ...

Institute of Electrical and Electronics Engineers Inc.2024

Advancing Graphene Imaging for Clear Identification of Lattice Defects: The Application of Revolve Sphere Levelling to Scanning Tunnelling Microscopy Images

Disha Bandyopadhyay

Application of revolve sphere levelling (RSL) as a practical and effective image processing tool for enhancing scanning tunnelling microscopy (STM) images of graphene atomic lattices is presented. Low-cost, ambient, and non-invasive STM methods overcome li ...

AMER CHEMICAL SOC2024

Data and scripts for the RaFSIP scheme

Athanasios Nenes, Paraskevi Georgakaki

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Zenodo2024

Toward Reliable Human Pose Forecasting With Uncertainty

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

2024

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

Deep learning-based temporal deconvolution for photon time-of-flight distribution retrieval

Edoardo Charbon, Claudio Bruschini, Arin Can Ülkü

The acquisition of the time of flight (ToF) of photons has found numerous applications in the biomedical field. Over the last decades, a few strategies have been proposed to deconvolve the temporal instrument response function (IRF) that distorts the exper ...

2024

Automated segmentation and labeling of subcutaneous mouse implants at 14.1T

Gilles Bioley, Dimitri Nestor Alice Van De Ville, Cristina Ramona Cudalbu Moldovan, Maria Giulia Preti, Nicolas Gninenko

Magnetic resonance imaging (MRI) is a valuable tool for studying subcutaneous implants in rodents, providing non-invasive insight into biomaterial conformability and longitudinal characterization. However, considerable variability in existing image analysi ...

FRONTIERS MEDIA SA2023

Communication-efficient distributed training of machine learning models

Thijs Vogels

In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...

EPFL2023

Third-harmonic generation monitoring of femtosecond-laser-induced in-volume functional modifications

Christian Enz, Yves Bellouard, Assim Boukhayma, Olivier Bernard, Andrea Kraxner

During the last two decades, ultrafast in-volume laser-based processing of transparent materials has emerged as a key 3D-printing method for manufacturing a variety of complex integrated photonic devices and micro-parts. Yet, identifying suitable laser pro ...

2023

Electron imaging of gas diffusion electrodes for proton exchange membrane fuel cells

Michele Bozzetti

The current energy crisis demands the development of new sustainable energy sources and devices with low environmental impact, including in the field of electrochemical cells. Mass transport limitations can reduce the overall performance of the device by l ...

EPFL2023

Enhancing Epileptic Seizure Detection with EEG Feature Embeddings

Mahsa Shoaran, Bingzhao Zhu

Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering neurostimulation to r ...

ArXiv2023

Overflow-free compute memories for edge AI acceleration

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

2023

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Bowen Huang

In the field of image acquisition, Dynamic Vision Sensors (DVS) present an innovative methodology, capturing only the variations in pixel brightness instead of absolute values and thereby revealing unique features. Given that the primary deployment of DVS ...

2023

Learning Dynamics of Spring-Mass Models with Physics-Informed Graph Neural Networks

Olga Fink, Vinay Sharma

We propose a physics-informed message-passing graph neural network (GNN) for learning the dynamics of springmass systems. The proposed method embeds the underlying physics directly into the message-passing scheme of the GNN. We compare the new scheme with ...

Research Publishing2023

Powering the social brain: Mitochondria in social behaviour

Silvie Rosalie Ruigrok, Maria del Carmen Sandi Perez, Dogukan Hazar Ülgen

A central role of brain mitochondria in regulating and influencing social behaviour is emerging. In addition to its important roles as the "powerhouses" of the cell, mitochondria possess a plethora of cellular functions, such as regulating ion homeostasis, ...

2023