Publications related to Earth observation satellite

Improving Few-Shot Object Detection with Object Part Proposals

Devis Tuia, Marc Conrad Russwurm, Arthur Chevalley

Few-Shot Object Detection (FSOD) allows fast adaptation of an object detection model to new classes of objects using few examples per class. This has many applications, in particular in satellite and aerial observation, as it allows learning from experts w ...

The Institute of Electrical and Electronics Engineers, Inc2023

Meteor: Meta-learning connecting earth problems observed from space

Devis Tuia, Benjamin Alexander Kellenberger, Marc Conrad Russwurm

Satellite remote sensing has become a key technology for monitoring Earth and the processes occurring at its surface. It relies on state-of-the-art machine learning models that require large annotated datasets to capture the extreme diversity of the proble ...

2023

Multi-task prompt-RSVQA to explicitly count objects on aerial images

Devis Tuia, Sylvain Lobry, Christel Marie Tartini-Chappuis, Javiera Francisca Castillo Navarro, Nicola Antonio Santacroce

Introduced to enable a wider use of Earth Observation images using natural language, Remote Sensing Visual Question Answering (RSVQA) remains a challenging task, in particular for questions related to counting. To address this specific challenge, we propos ...

2023

Frontiers in the Application of RF Vacuum Electronics

Timothy Goodman

The application of radio frequency (RF) vacuum electronics for the betterment of the human condition began soon after the invention of the first vacuum tubes in the 1920s and has not stopped since. Today, microwave vacuum devices are powering important app ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Towards reliable retrievals of cloud droplet number for non-precipitating planetary boundary layer clouds and their susceptibility to aerosol

Athanasios Nenes, Paraskevi Georgakaki, Romanos Foskinis

Remote sensing has been a key resource for developing extensive and detailed datasets for studying and constraining aerosol-cloud-climate interactions. However, aerosol-cloud collocation challenges, algorithm limitations, as well as difficulties in unravel ...

FRONTIERS MEDIA SA2022

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Tamar Kohn, Alfred Johny Wüest, Damien Bouffard, Chaojie Li

Propelled by the rapid development of equipment, technology and computational power, the monitoring and simulation of the hydrodynamics in lakes have steadily advanced. In contrast, water quality simulations are more difficult to implement, due to the diff ...

Elsevier2022

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

Yinlin Hu, Yunpeng Li, Jingyu Li, Rui Song

Semantic segmentation for remote sensing images (RSI) is critical for the Earth monitoring system. However, the covariate shift between RSI datasets under different capture conditions cannot be alleviated by directly using the unsupervised domain adaptatio ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Devis Tuia, Marc Conrad Russwurm

Learning to predict accurately from a few data samples is a central challenge in modern data-hungry machine learning. On natural images, human vision typically outperforms deep learning approaches on few-shot learning. However, we hypothesize that aerial a ...

IEEE2022

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Earth observation satellite

Improving Few-Shot Object Detection with Object Part Proposals

Meteor: Meta-learning connecting earth problems observed from space

Multi-task prompt-RSVQA to explicitly count objects on aerial images

Frontiers in the Application of RF Vacuum Electronics

Towards reliable retrievals of cloud droplet number for non-precipitating planetary boundary layer clouds and their susceptibility to aerosol

Remote sensing visual question answering with a self-attention multi-modal encoder

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica

Graph Chatbot

Chat with Graph Search

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

Multi-task prompt-RSVQA to explicitly count objects on aerial images

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Remote sensing visual question answering with a self-attention multi-modal encoder

Meteor: Meta-learning connecting earth problems observed from space

Towards reliable retrievals of cloud droplet number for non-precipitating planetary boundary layer clouds and their susceptibility to aerosol

Frontiers in the Application of RF Vacuum Electronics

Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica

Improving Few-Shot Object Detection with Object Part Proposals