Publication

Preventing Breaks in Embodiment in Immersive Virtual Reality

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Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023

Reinforcement learning approach to control an inverted pendulum: A general framework for educational purposes

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Machine learning is often cited as a new paradigm in control theory, but is also often viewed as empirical and less intuitive for students than classical model-based methods. This is particularly the case for reinforcement learning, an approach that does n ...

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Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

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Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

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Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

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Metal-based Laser Powder Bed Fusion (LPBF) has made fabricating intricate components easier. Yet, assessing part quality is inefficient, relying on costly Computed Tomography (CT) scans or time-consuming destructive tests. Also, intermittent inspection of ...

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'connEcted caesarean section': creating a virtual link between MOthers and their infanTs to ImprOve maternal childbirth experieNce - study protocol for a PILOT trial (e-motion-pilot)

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IntroductionOne-third of mothers rate their childbirth as traumatic. The prevalence of childbirth-related post-traumatic stress disorder (CB-PTSD) is 4.7%. Skin-to-skin contact is a protective factor against CB-PTSD. However, during a caesarean section (CS ...

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Cybersickness still poses a significant challenge to the widespread usage of virtual reality (VR), leading to different levels of discomfort and potentially breaking the immersive experience. Researchers have attempted to discover the possible fundamental ...

EPFL2023

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International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really gener ...

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Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

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Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

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Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

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Laser Powder Bed Fusion (LPBF) is an Additive Manufacturing (AM) process consolidating parts layer by layer, from a metallic powder bed. It allows no limitation in terms of geometry and is therefore of particular interest to various industries. Metallic LP ...

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Enhancing Epileptic Seizure Detection with EEG Feature Embeddings

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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 ...

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Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

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Robustness of medical image classification models is limited by its exposure to the candidate disease classes. Generalized zero shot learning (GZSL) aims at correctly predicting seen and unseen classes and most current GZSL approaches have focused on the s ...

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