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Devis Tuia

Cette personne a quitté l’EPFL

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Publications associées (151)

Page 6 sur 8

Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward

Devis Tuia

Earth observation (EO) is increasingly used for mapping and monitoring processes occurring at the surface of Earth. Data acquired by satellites nowadays allow us to have a global view, consistent in time, of the state of our forests, oceans, and growing ur ...

Institute of Electrical and Electronics Engineers (IEEE)2024

Blue ice in Antarctica: The gateway to travel in time and space

Devis Tuia, Marc Conrad Russwurm, Benjamin Alexander Kellenberger

Antarctica has unique areas that expose blue ice, which contrast to most of the continent (~98%) that is covered by snow. Some of these blue ice areas (BIAs) contain meteorite concentrations and (very) old ice, making them very valuable for understanding o ...

GFZ German Research Centre for Geosciences2023

Discovering relevant spatial filterbanks for VHR image classification

Devis Tuia

In very high resolution (VHR) image classification it is common to use spatial filters to enhance the discrimination among landuses related to similar spectral properties but different spatial characteristics. However, the filters types that can be used ar ...

IEEE2012

Wasserstein Adversarial Regularization for learning with label noise

Devis Tuia

Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we propose ...

2021

Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation

Devis Tuia, Emanuele Dalsasso, Hugo Laurent Pascal Porta

Prototypical part learning is emerging as a promising approach for making semantic segmentation interpretable. The model selects real patches seen during training as prototypes and constructs the dense prediction map based on the similarity between parts o ...

IEEE2025

Domain adaptation in remote sensing through cross-image synthesis with dictionaries

Devis Tuia, Frank Grégoire Jean de Morsier, Giona Matasci

2014

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

Devis Tuia

Visual Question Answering (VQA) on remote sensing imagery can help non-expert users in extracting information from Earth observation data. Current approaches follow a neural encoder-decoder design, combining convolutional and recurrent encoders together wi ...

2022

Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images

Devis Tuia, Benjamin Alexander Kellenberger

Automated animal censuses with aerial imagery are a vital ingredient towards wildlife conservation. Recent models are generally based on deep learning and thus require vast amounts of training data. Due to their scarcity and minuscule size, annotating anim ...

IEEE2021

RSVQA Meets Bigearthnet: A New, Large-Scale, Visual Question Answering Dataset for Remote Sensing

Devis Tuia

Visual Question Answering is a new task that can facilitate the extraction of information from images through textual queries: it aims at answering an open-ended question formulated in natural language about a given image. In this work, we introduce a new ...

IEEE2021

Forest Drought Impact Prediction based on Spatio-temporal Satellite Imagery and Weather Forecasts -- A Spatio-Temporal Approach using Convolutional LSTM Models

Devis Tuia

2023

Meteor: Meta-learning connecting earth problems observed from space

Devis Tuia, Marc Conrad Russwurm, Benjamin Alexander Kellenberger

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

Self-supervised Change Detection via Cooperative Learning: A Two-Player Model

Manon Cécile Nicole Béchaz, Devis Tuia, Emanuele Dalsasso

Change detection (CD) is a critical task in remote sensing, especially for monitoring dynamic urban environments. In this work, we present a novel, self-supervised CD approach that leverages a two-player architecture to improve the reliability and accuracy ...

IEEE2025

Large-scale detection of marine debris in coastal areas with Sentinel-2

Sushen Jilla Venkatesa, Devis Tuia, Marc Conrad Russwurm

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Here, remote sensing can provide reliable estimates of plastic pollution by regularly monitoring and d ...

Cell Press2023

High-resolution population maps derived from Sentinel-1 and Sentinel-2

Devis Tuia

Detailed population maps play an important role in diverse fields ranging from humanitarian action to urban planning. Generating such maps in a timely and scalable manner presents a challenge, especially in datascarce regions. To address it we have develop ...

Springer Science and Business Media LLC2024

Detection of Settlements in Tanzania and Mozambique by Many Regional Few-Shot Models

Devis Tuia, Marc Conrad Russwurm, Lloyd Haydn Hughes

In this work, we propose an approach to aid in mapping small settlements, which are often misclassified by models trained on a large-scale context (global or regional). We leverage pre-trained land cover models and few-shot learning to enhance the detectio ...

2023

Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current Approaches, Open Challenges, and Future Opportunities

Devis Tuia

2022

Urban Visual-spatial Intelligence: Linking Human and Sensor Perception for Sustainable Urban Development

Devis Tuia

Understanding urban perception enhances urban intelligence research, aiding sustainable development and smart city. Urban Visual-Spatial Intelligence (UVSI) integrates human and sensor perception. This Perspective explores UVSI's potential for sustainable ...

SPRINGERNATURE2025

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

Nicola Antonio Santacroce, Devis Tuia, Christel Marie Tartini-Chappuis, Javiera Francisca Castillo Navarro, Charlotte Louise Sertic

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

Estimating Uncertainty of Point-Cloud Based Single-Tree Segmentation with Ensemble Based Filtering

Devis Tuia, Matthew Josef Parkan

2018

Muti-modal learning in photogrammetry and remote sensing

Devis Tuia

ELSEVIER2021