Recherche

Afficher tous les résultats pour

Accueil

Personne

Devis Tuia

Cette personne a quitté l’EPFL

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (151)

Page 5 sur 8

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Michael Lehning, Devis Tuia, Yael Frischholz

To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

2025

MaskSDM: Adaptive Species Distribution Modeling Through Data Masking

Devis Tuia, Nina Marion Aurélia Van Tiel, Robin Adrien Zbinden, Gencer Sümbül

Species distribution models (SDMs) correlate species occurrences with environmental conditions and underpin much of ecological research. A key consideration in developing SDMs is selecting the optimal set of environmental predictor variables, which vary de ...

Springer Science and Business Media Deutschland GmbH2025

Training Techniques for Presence-Only Habitat Suitability Mapping with Deep Learning

Devis Tuia, Benjamin Alexander Kellenberger

The goal of habitat suitability mapping is to predict the lo-cations in which a given species could be present. This is typically accomplished by statistical models which use envi-ronmental variables to predict species observation data. The relationship be ...

IEEE2022

Segmenting Without Annotating: Crack Segmentation and Monitoring via Post-Hoc Classifier Explanations

Devis Tuia, Olga Fink, Florent Evariste Forest, Hugo Laurent Pascal Porta

Monitoring the cracks in walls, roads and other types of infrastructure is essential to ensure the safety of a structure, and plays an important role in structural health monitoring. Automatic visual inspection allows an efficient, costeffective and safe h ...

Research Publishing2023

Knowledge-Aware Text–Image Retrieval for Remote Sensing Images

Devis Tuia, Javiera Francisca Castillo Navarro, Li Mi

Image-based retrieval in large Earth observation archives is challenging because one needs to navigate across thousands of candidate matches only with the query image as a guide. By using text as information supporting the visual query, the retrieval syste ...

Institute of Electrical and Electronics Engineers (IEEE)2024

Deep Learning‐based Semantic Segmentation in Remote Sensing

Devis Tuia

Semantic segmentation consists of the generation of a categorical map, given an image in which each pixel of the image is automatically assigned a class. Deep learning allows the influence of the pixel's context to be learned by capturing the non-linear re ...

Wiley2021

Crop Backscatter Modeling And Soil Moisture Estimation With Support Vector Regression

Jean-Philippe Thiran, Devis Tuia, Maurice Borgeaud, Jelena Stamenkovic

In this paper, we used an improved version of the Tor Vergata radiative transfer model to simulate the backscattering coefficient for the L-band SAR signals over areas covered with vegetation. Fields of winter wheat, maize and sugar beet observed during th ...

Ieee2014

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

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

Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence and is limited ...

Elsevier2024

Attribute Prediction as Multiple Instance Learning

Devis Tuia, Diego Marcos Gonzalez

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

Journal of Machine Learning Research Inc.2022

Social media and deep learning reveal specific cultural preferences for biodiversity

Devis Tuia

Social media has created new opportunities to map cultural ecosystem services (CES) related to biodiversity at large scales. However, using these novel data to understand people's preferences in relation to these CES remains a challenge. To address this, w ...

2023

Putting the user into the active learning loop: towards realistic but efficient photointerpretation

Devis Tuia

In recent years, several studies have been published about the smart definition of training set using active learning algorithms. However, none of these works consider the contradiction between the active learning methods, which rank the pixels according t ...

Ieee2012

Short-term runoff forecasting in an alpine catchment with a long short-term memory neural network

Devis Tuia, Marc Conrad Russwurm

The governing hydrological processes are expected to shift under climate change in the alpine regions of Switzerland. This raises the need for more adaptive and accurate methods to estimate river flow. In high-altitude catchments influenced by snow and gla ...

2023

Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences

Devis Tuia

Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered a ...

Wiley2021

Social media and deep learning capture the aesthetic quality of the landscape

Devis Tuia

Peoples’ recreation and well-being are closely related to their aesthetic enjoyment of the landscape. Ecosystem service (ES) assessments record the aesthetic contributions of landscapes to peoples’ well-being in support of sustainable policy goals. However ...

Nature Research2021

Towards Efficient Correction of Coconut Tree Detection Errors

Devis Tuia

Coconut tree plantations are one of the main sources of income in several South Pacific countries. Thus, keeping track of the location of coconut trees is important for monitoring and post-disaster assessment. Although deep learning based object detectors ...

IEEE2022

Detection of Floods In Sar Images with Non-Linear Kernel Clustering and Topographic Prior

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

After a major flood catastrophe, a precious information is the delineation of the affected areas. Remote sensing imagery, especially synthetic aperture radar, allows to obtain a global and complete view of the situation. However, the detection of the flood ...

2013

Data for Paper "Scalable Semantic 3D Mapping of Coral Reefs with Deep Learning"

Anders Meibom, Devis Tuia, Guilhem Maurice Louis Banc-Prandi, Jonathan Paul Sauder

Example Data for DeepReefMap This dataset contains input videos in MP4 format taken with GoPro Hero 10 Cameras in Reefs in the Red Sea to demonstrate the DeepReefMap tool, which is described in the paper "Scalable Semantic 3D Mapping of Coral Reefs with De ...

EPFL Infoscience2024

OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing

Devis Tuia

OpenStreetMap (OSM) is a community-based, freely available, editable map service created as an alternative to authoritative sources. Given that it is edited mainly by volunteers with different mapping skills, the completeness and quality of its annotations ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

POLO – Point-Based, Multi-class Animal Detection

Devis Tuia, Emanuele Dalsasso, Giacomo Günter May

Automated wildlife surveys based on drone imagery and object detection technology are a powerful and increasingly popular tool in conservation biology. Most detectors require training images with annotated bounding boxes, which are tedious, expensive, and ...

Springer Science and Business Media Deutschland GmbH2025

Non-linear Low-rank and Sparse Representation for Hyperspectral Image Analysis

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

In this paper, we tackle the problem of unsupervised classification of hyperspectral images. We propose a clustering method based on graphs representing the data structure, which is assumed to be an union of multiple manifolds. The method constraints the p ...

2014