Publications related to Sensefly

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Harmful chemical compounds are released daily in warehouses, chemical plants and during environmental emergencies. Their uncontrolled dispersion contributes to the pollution of the atmosphere and threatens human and animal lives. When gas leaks occur, the ...

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 ...

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

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

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

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. ...

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

Crop maps are crucial for agricultural monitoring and food management and can additionally support domain-specific applications, such as setting cold supply chain infrastructure in developing countries. Machine learning (ML) models, combined with freely-av ...

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 ...

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 ...

Flapping wings produce lift and thrust in bio-inspired aerial robots, leading to quiet, safe and efficient flight. However, to extend their application scope, these robots must perch and land, a feat widely demonstrated by birds. Despite recent progress, f ...

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 ...

Some governance functions traditionally performed by humans are increasingly informed and sometimes automatically executed by machine learning algorithms (governance by machine learning) to benefit society. Therefore, it is necessary to think also about th ...

Pixelation is common in quantum imaging systems and limit the image spatial resolution. Here, the authors introduce a pixel super-resolution approach based on measuring the full spatially-resolved joint probability distribution of spatially-entangled photo ...

Introduction: Imaging studies are used to guide patient selection for acute stroke treatment. Perfusion CT (pCT) is widely used to identify the acute ischemic core and penumbra, but the prediction of the final infarct remains challenging. With the advent o ...

Image super-resolution reconstructs a higher-resolution image from the observed low-resolution image. In recent years, machine learning models have been widely employed and deep learning networks have achieved state-of-the-art super-resolution performance. ...

Small-scale drones have enough sensing and computing power to find use across a growing number of applications. However, flying in the low-Reynolds number regime remains challenging. High sensitivity to atmospheric turbulence compromises vehicle stability ...

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 ...

High levels of cognitive workload decreases human's performance and leads to failures with catastrophic outcomes in risky missions. Today, reliable cognitive workload detection presents a common major challenge, since the workload is not directly observabl ...

Sensefly

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Gas Sensing with Rotary-Wing Nano Aerial Vehicles

Meta-learning to address diverse Earth observation problems across resolutions

Timelapse: Rhone mouth in Geneva Lake - 2017

Timelapse: Geneva Lake, in front of Chexbres - 2019

Timelapse: Rhone mouth in Geneva Lake - 2019

Timelapse: Rhone mouth in Geneva Lake - 2021

Timelapse: Rhone mouth in Geneva Lake - 2023

Timelapse: Rhone mouth in Geneva Lake - 2022

Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region

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

MultiMAE: Multi-modal Multi-task Masked Autoencoders

How ornithopters can perch autonomously on a branch

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

Nine recommendations for the governance of AI systems

Pixel super-resolution with spatially entangled photons

Deep Learning Building on Prior Ischemic Core Segmentation Improves Prediction of Infarction After Stroke

Towards Real-World Super-Resolution using Deep Neural Networks

A bioinspired Separated Flow wing provides turbulence resilience and aerodynamic efficiency for miniature drones

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

Real-Time Cognitive Workload Monitoring Based on Machine Learning Using Physiological Signals in Rescue Missions