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Related publications (27)

Stellar Metallicities and Gradients in the Isolated, Quenched Low-mass Galaxy Tucana

Nicolas Lawrence Etienne Longeard

We measure the metallicities of 374 red giant branch (RGB) stars in the isolated, quenched dwarf galaxy Tucana using Hubble Space Telescope (HST) narrow-band (F395N) Calcium H & K (CaHK) imaging. Our sample is a factor of similar to 7 similar to 7 larger t ...

Iop Publishing Ltd2024

Timelapse: Rhone mouth in Geneva Lake - 2017

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2017. ...

EPFL Infoscience2023

Timelapse: Geneva Lake, in front of Chexbres - 2019

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2019. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2019

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2019. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2021

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2021. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2023

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute from January to August 2023. ...

EPFL Infoscience2023

Timelapse: Rhone mouth in Geneva Lake - 2022

Valentin Kindschi

The dataset is a collection of RGB and thermal images of the Rhone mouth in Geneva Lake, taken every minute in 2022. ...

EPFL Infoscience2023

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Alexandre Massoud Alahi, Dolaana Khovalyg, Mohamad Rida, Mohamed Ossama Ahmed Abdelfattah

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

2023

Non-intrusive physiological parameters sensing for personalized human thermal comfort prediction

Alexandre Massoud Alahi, Dolaana Khovalyg, Mohamad Rida, Mohamed Ossama Ahmed Abdelfattah

Sensing and projecting an individual’s human thermal comfort in buildings is a complex but crucial task for transitioning toward human-centered indoor climate control. Non-intrusive collection of physiological and personal information from the human body, ...

2023

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Amir Roshan Zamir, Roman Christian Bachmann, Andrei Atanov, David Mizrahi

We propose a pre-training strategy called Multi-modal Multi-task Masked Autoencoders (MultiMAE). It differs from standard Masked Autoencoding in two key aspects: I) it can optionally accept additional modalities of information in the input besides the RGB ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Deploying an Instance Segmentation Algorithm to Implement Social Distancing for Prosthetic Vision

Silvestro Micera

The COVID-19 pandemic outbreak is causing a dramatic worsening in the already complicated living conditions of blind and visually impaired individuals. Social distancing is the most effective strategy to limit virus spread, but is extremely difficult for b ...

IEEE2022

Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions

Mathieu Salzmann, Vincent Lepetit, Yinlin Hu

We present a method that can recognize new objects and estimate their 3D pose in RGB images even under partial occlusions. Our method requires neither a training phase on these objects nor real images depicting them, only their CAD models. It relies on a s ...

IEEE COMPUTER SOC2022

Learning to Simulate Realistic LiDARs

Pascal Fua, Benoît Alain René Guillard

Simulating realistic sensors is a challenging part in data generation for autonomous systems, often involving carefully handcrafted sensor design, scene properties, and physics modeling. To alleviate this, we introduce a pipeline for data-driven simulation ...

2022

Multi-View Shape Estimation of Transparent Containers

Pascal Frossard, Apostolos Modas, Andrea Cavallaro

The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions. In this paper, we propose a method for jointly localising container-like obj ...

IEEE2020

Aliasing mitigation in optical microscopy of dynamic biological samples by use of temporally modulated color illumination and a standard RGB camera

Michael Stefan Daniel Liebling, Christian Jaques

Significance: Despite recent developments in microscopy, temporal aliasing can arise when imaging dynamic samples. Modern sampling frameworks, such as generalized sampling, mitigate aliasing but require measurement of temporally overlapping and potentially ...

SPIE Society of Photo-optical Instrumentation Engineers2020

Learning One Class Representations for Face Presentation Attack Detection using Multi-channel Convolutional Neural Networks

Sébastien Marcel

Face recognition has evolved as a widely used biometric modality. However, its vulnerability against presentation attacks poses a significant security threat. Though presentation attack detection (PAD) methods try to address this issue, they often fail in ...

IEEE2020

Single-Sensor Source Localization Using Electromagnetic Time Reversal and Deep Transfer Learning: Application to Lightning

Farhad Rachidi-Haeri, Marcos Rubinstein, Mohammad Azadifar, Amirhossein Mostajabi, Hamidreza Karami, Alireza Ghasemi

Electromagnetic Time Reversal (EMTR) has been used to locate different types of electromagnetic sources. We propose a novel technique based on the combination of EMTR and Machine Learning (ML) for source localization. We show for the first time that ML tec ...

Springer Nature2019

Deep Semantic Segmentation Using Nir As Extra Physical Information

Sabine Süsstrunk, Siavash Arjomand Bigdeli

Deep neural networks for semantic segmentation are most often trained with RGB color images, which encode the radiation visible to the human eyes. In this paper, we study if additional physical scene information, specifically Near-Infrared (NIR) images, im ...

IEEE2019

Wide Gamut Spectral Upsampling with Fluorescence

Wenzel Alban Jakob

Physically based spectral rendering has become increasingly important in recent years. However, asset textures in such systems are usually still drawn or acquired as RGB tristimulus values. While a number of RGB to spectrum upsampling techniques are availa ...

2019

Temporal Super-Resolution Microscopy Using a Hue-Encoded Shutter

Sylvain Calinon, Michael Stefan Daniel Liebling, Emmanuel Pignat, Christian Jaques

Limited time-resolution in microscopy is an obstacle to many biological studies. Despite recent advances in hardware, digital cameras have limited operation modes that constrain frame-rate, integration time, and color sensing patterns. In this paper, we pr ...

2019