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Devis Tuia

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Publications associées (151)

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Detecting animals in African Savanna with UAVs and the crowds

Devis Tuia, Stéphane Joost

Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife monitoring, with several advantages over traditional field-based methods. They have readily been used to count birds, marine mammals and large herbivores in different environments, tasks ...

Elsevier2017

Concept Discovery for The Interpretation of Landscape Scenicness

Devis Tuia

In this paper, we study how to extract visual concepts to understand landscape scenicness. Using visual feature representations from a Convolutional Neural Network (CNN), we learn a number of Concept Activation Vectors (CAV) aligned with semantic concepts ...

2020

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Devis Tuia, Marc Conrad Russwurm, Thiên-Anh Claris Nguyen, Gaston Jean Lenczner

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Elsevier Science Inc2024

Geoinformation Harvesting From Social Media Data: A community remote sensing approach

Devis Tuia

As unconventional sources of geoinformation, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multiperspective stream, but with unknown and diverse quality. Due to its complementarity to rem ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Discovering single classes in remote sensing images with active learning

Devis Tuia

When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. More ...

2012

Semisupervised Classification of Remote Sensing Images With Hierarchical Spatial Similarity

Devis Tuia

A semisupervised kernel deformation function, including spatial similarity, is proposed for the classification of remote sensing (RS) images. The method exploits the characteristic of these images, in which spatially nearby points are likely to belong to t ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Pose estimation of landscape images using DEM and orthophotos

Devis Tuia, François Golay, Christoph Strecha, Timothée Produit

In this paper, we propose a methodology for the estimation of the pose of oblique landscape images. Knowledge about the pose is needed for using such images in augmented reality applications or to allow projection of pixels in a GIS for spatial analysis. W ...

2012

Hydrometeor classification from polarimetric radar measurements: a clustering approach

Alexis Berne, Devis Tuia, Jacopo Grazioli

A data-driven approach to the classification of hydrometeors from measurements collected with polarimetric weather radars is proposed. In a first step, the optimal number of hydrometeor classes (nopt) that can be reliably identified from a large set of pol ...

Copernicus Gesellschaft Mbh2015

Exploring neural networks and their potential for species distribution modeling

Devis Tuia, Benjamin Alexander Kellenberger, Nina Marion Aurélia Van Tiel, Lloyd Haydn Hughes, Robin Adrien Zbinden

Species distribution models (SDMs) relate species occurrence data with environmental variables and are used to understand and predict species distributions across landscapes. While some machine learning models have been adopted by the SDM community, recent ...

2023

Semantic Segmentation of Coffee Plantations from Sentinel-2 Time Series

Devis Tuia, Jan Pisl, Gaston Jean Lenczner

Coffee production serves as an important source of income for millions of farmers across many tropical countries. Given the scale of the production, accurate and up-to-date maps of coffee plantations are needed to detect, monitor, and mitigate potential ne ...

Institute of Electrical and Electronics Engineers Inc.2024

End-to-end learned early classification of time series for in-season crop type mapping

Devis Tuia

Remote sensing satellites capture the cyclic dynamics of our Planet in regular time intervals recorded in satellite time series data. End-to-end trained deep learning models use this time series data to make predictions at a large scale, for instance, to p ...

2023

Unsupervised Change Detection via Hierarchical Support Vector Clustering

Jean-Philippe Thiran, Devis Tuia, Volker Gass, Frank Grégoire Jean de Morsier, Maurice Borgeaud

When dealing with change detection problems, information about the nature of the changes is often unavailable. In this paper we propose a solution to perform unsupervised change detection based on nonlinear support vector clustering. We build a series of n ...

2012

Estimation of Soil Moisture from Airborne Hyperspectral Imagery with Support Vector Regression

Jean-Philippe Thiran, Devis Tuia, Frank Grégoire Jean de Morsier, Maurice Borgeaud, Jelena Stamenkovic

In this paper, we propose to estimate soil moisture in bare soils directly from hyperspectral imagery using support vector regression (nu-SVR). nu-SVR is a supervised non-parametric learning technique, e.g. making no assumption on the underlying data distr ...

2013

MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

Devis Tuia, Alexander Mathis, Valentin Alexandre Guy Gabeff

MammAlps is a multimodal and multi-view dataset of wildlife behavior monitoring. Nine camera-traps were placed at three monitoring sites in the Swiss National Park, from which we curated over 14 hours of video with audio, 2D segmentation maps and 8.5 hours ...

Zenodo2025

Cross-Modal Learning of Housing Quality in Amsterdam

Devis Tuia

In our research we test data and models for the recognition of housing quality in the city of Amsterdam from ground-level and aerial imagery. For ground-level images we compare Google StreetView (GSV) to Flickr images. Our results show that GSV predicts th ...

ACM2021

Time Series Analysis of Urban Liveability

Devis Tuia, Diego Marcos Gonzalez

In this paper we explore deep learning models to monitor longitudinal liveability changes in Dutch cities at the neighbourhood level. Our liveability reference data is defined by a country-wise yearly survey based on a set of indicators combined into a liv ...

IEEE2023

Deep Domain Adaptation in Earth Observation

Devis Tuia, Benjamin Alexander Kellenberger

When applied to new datasets, acquired at different time moments, with different sensors or under different acquisition conditions, deep learning models might fail spectacularly. This is because they have learned from the data distribution observed during ...

Wiley2021

Pose Estimation of Web-Shared Landscape Pictures

Devis Tuia, Vincent Lepetit, François Golay, Timothée Produit

We propose a robust method for registering high oblique images of landscapes. Typically, an input image can be registered by matching it against a set of registered images of the same location. While this has been shown to work very well for images of popu ...

2014

Estimating Fine-Grained Population Growth Rates from Coarse Census Data

Devis Tuia

Fine-grained population estimation is important for several domains, such as urban planning, public health, and humanitarian action. Due to limited resources, population maps with sufficient spatial resolution and temporal frequency are not available for m ...

Institute of Electrical and Electronics Engineers Inc.2024

Language Transformers for Remote Sensing Visual Question Answering

Devis Tuia, Vincent Alexandre Mendez, Christel Marie Tartini-Chappuis

Remote sensing visual question answering (RSVQA) opens new avenues to promote the use of satellites data, by interfacing satellite image analysis with natural language processing. Capitalizing on the remarkable advances in natural language processing and c ...

IEEE2022