b'Devis Tuia'

research

∙ 09/20/2023

From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring

Monitoring surface cracks in infrastructure is crucial for structural he...

0 Florent Forest, et al. ∙

research

∙ 09/01/2023

Time Series Analysis of Urban Liveability

In this paper we explore deep learning models to monitor longitudinal li...

0 Alex Levering, et al. ∙

research

∙ 07/05/2023

Large-scale Detection of Marine Debris in Coastal Areas with Sentinel-2

Detecting and quantifying marine pollution and macro-plastics is an incr...

0 Marc Rußwurm, et al. ∙

research

∙ 05/15/2023

Artificial intelligence to advance Earth observation: a perspective

Earth observation (EO) is a prime instrument for monitoring land and oce...

0 Devis Tuia, et al. ∙

research

∙ 11/08/2022

Fine-grained Population Mapping from Coarse Census Counts and Open Geodata

Fine-grained population maps are needed in several domains, like urban p...

7 Nando Metzger, et al. ∙

research

∙ 11/01/2022

Geo-Information Harvesting from Social Media Data

As unconventional sources of geo-information, massive imagery and text m...

0 Xiao Xiang Zhu, et al. ∙

research

∙ 12/21/2021

Deep Learning and Earth Observation to Support the Sustainable Development Goals

The synergistic combination of deep learning models and Earth observatio...

16 Claudio Persello, et al. ∙

research

∙ 10/25/2021

Seeing biodiversity: perspectives in machine learning for wildlife conservation

Data acquisition in animal ecology is rapidly accelerating due to inexpe...

42 Devis Tuia, et al. ∙

research

∙ 09/24/2021

How to find a good image-text embedding for remote sensing visual question answering?

Visual question answering (VQA) has recently been introduced to remote s...

0 Christel Chappuis, et al. ∙

research

∙ 08/17/2021

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

Automated animal censuses with aerial imagery are a vital ingredient tow...

0 Xiaochen Zheng, et al. ∙

research

∙ 07/29/2021

Mapping Vulnerable Populations with AI

Humanitarian actions require accurate information to efficiently delegat...

9 Benjamin Kellenberger, et al. ∙

research

∙ 04/15/2021

Semisupervised Manifold Alignment of Multimodal Remote Sensing Images

We introduce a method for manifold alignment of different modalities (or...

0 Devis Tuia, et al. ∙

research

∙ 04/15/2021

Learning User's confidence for active learning

In this paper, we study the applicability of active learning in operativ...

0 Devis Tuia, et al. ∙

research

∙ 04/15/2021

A survey of active learning algorithms for supervised remote sensing image classification

Defining an efficient training set is one of the most delicate phases fo...

0 Devis Tuia, et al. ∙

research

∙ 04/15/2021

Recent Advances in Domain Adaptation for the Classification of Remote Sensing Data

The success of supervised classification of remotely sensed images acqui...

0 Devis Tuia, et al. ∙

research

∙ 04/11/2021

Towards a Collective Agenda on AI for Earth Science Data Analysis

In the last years we have witnessed the fields of geosciences and remote...

0 Devis Tuia, et al. ∙

research

∙ 01/20/2021

Self-supervised pre-training enhances change detection in Sentinel-2 imagery

While annotated images for change detection using satellite imagery are ...

0 Marrit Leenstra, et al. ∙

research

∙ 01/10/2021

Semantic Segmentation of Remote Sensing Images with Sparse Annotations

Training Convolutional Neural Networks (CNNs) for very high resolution i...

8 Yuansheng Hua, et al. ∙

research

∙ 12/07/2020

Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization

Remote sensing image classification exploiting multiple sensors is a ver...

0 Devis Tuia, et al. ∙

research

∙ 09/18/2020

Contextual Semantic Interpretability

Convolutional neural networks (CNN) are known to learn an image represen...

12 Diego Marcos, et al. ∙

research

∙ 09/17/2020

Deploying machine learning to assist digital humanitarians: making image annotation in OpenStreetMap more efficient

Locating populations in rural areas of developing countries has attracte...

18 John E. Vargas-Muñoz, et al. ∙

research

∙ 07/13/2020

OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing

OpenStreetMap (OSM) is a community-based, freely available, editable map...

12 John Vargas, et al. ∙

research

∙ 04/24/2020

Detecting Unsigned Physical Road Incidents from Driver-View Images

Safety on roads is of uttermost importance, especially in the context of...

14 Alex Levering, et al. ∙

research

∙ 03/16/2020

RSVQA: Visual Question Answering for Remote Sensing Data

This paper introduces the task of visual question answering for remote s...

9 Sylvain Lobry, et al. ∙

research

∙ 09/18/2019

Semantically Interpretable Activation Maps: what-where-how explanations within CNNs

A main issue preventing the use of Convolutional Neural Networks (CNN) i...

6 Diego Marcos, et al. ∙

research

∙ 07/23/2019

Adaptive Compression-based Lifelong Learning

The problem of a deep learning model losing performance on a previously ...

0 Shivangi Srivastava, et al. ∙

research

∙ 07/17/2019

Half a Percent of Labels is Enough: Efficient Animal Detection in UAV Imagery using Deep CNNs and Active Learning

We present an Active Learning (AL) strategy for re-using a deep Convolut...

2 Benjamin Kellenberger, et al. ∙

research

∙ 05/05/2019

Understanding urban landuse from the above and ground perspectives: a deep learning, multimodal solution

Landuse characterization is important for urban planning. It is traditio...

0 Shivangi Srivastava, et al. ∙

research

∙ 04/08/2019

Pushing the right boundaries matters! Wasserstein Adversarial Training for Label Noise

Noisy labels often occur in vision datasets, especially when they are is...

16 Bharath Bhushan Damodaran, et al. ∙

research

∙ 01/24/2019

Correcting rural building annotations in OpenStreetMap using convolutional neural networks

Rural building mapping is paramount to support demographic studies and p...

0 John E. Vargas-Muñoz, et al. ∙

research

∙ 08/24/2018

Decision fusion with multiple spatial supports by conditional random fields

Classification of remotely sensed images into land cover or land use is ...

2 Devis Tuia, et al. ∙

research

∙ 08/23/2018

Deep multi-task learning for a geographically-regularized semantic segmentation of aerial images

When approaching the semantic segmentation of overhead imagery in the de...

0 Michele Volpi, et al. ∙

research

∙ 07/31/2018

Scale equivariance in CNNs with vector fields

We study the effect of injecting local scale equivariance into Convoluti...

0 Diego Marcos, et al. ∙

research

∙ 07/25/2018

Change Detection between Multimodal Remote Sensing Data Using Siamese CNN

Detecting topographic changes in the urban environment has always been a...

2 Zhenchao Zhang, et al. ∙

research

∙ 06/29/2018

Detecting Mammals in UAV Images: Best Practices to address a substantially Imbalanced Dataset with Deep Learning

Knowledge over the number of animals in large wildlife reserves is a vit...

2 Benjamin Kellenberger, et al. ∙

research

∙ 05/17/2018

DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images

We present the DeepGlobe 2018 Satellite Image Understanding Challenge, w...

3 Ilke Demir, et al. ∙

research

∙ 03/27/2018

DeepJDOT: Deep Joint distribution optimal transport for unsupervised domain adaptation

In computer vision, one is often confronted with problems of domain shif...

0 Bharath Bhushan Damodaran, et al. ∙

research

∙ 03/16/2018

Learning deep structured active contours end-to-end

The world is covered with millions of buildings, and precisely knowing e...

0 Diego Marcos, et al. ∙

research

∙ 03/16/2018

Land cover mapping at very high resolution with rotation equivariant CNNs: towards small yet accurate models

In remote sensing images, the absolute orientation of objects is arbitra...

0 Diego Marcos, et al. ∙

research

∙ 03/13/2018

Optimal Transport for Multi-source Domain Adaptation under Target Shift

In this paper, we propose to tackle the problem of reducing discrepancie...

0 Ievgen Redko, et al. ∙

research

∙ 10/11/2017

Deep learning in remote sensing: a review

Standing at the paradigm shift towards data-intensive science, machine l...

0 Xiao Xiang Zhu, et al. ∙

research

∙ 09/06/2017

Detecting animals in African Savanna with UAVs and the crowds

Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife mon...

0 Nicolas Rey, et al. ∙

research

∙ 05/23/2017

Towards seamless multi-view scene analysis from satellite to street-level

In this paper, we discuss and review how combined multi-view imagery fro...

0 Sébastien Lefèvre, et al. ∙

research

∙ 12/29/2016

Rotation equivariant vector field networks

In many computer vision tasks, we expect a particular behavior of the ou...

0 Diego Marcos, et al. ∙

research

∙ 08/02/2016

Dense semantic labeling of sub-decimeter resolution images with convolutional neural networks

Semantic labeling (or pixel-level land-cover classification) in ultra-hi...

0 Michele Volpi, et al. ∙

research

∙ 06/23/2016

Non-convex regularization in remote sensing

In this paper, we study the effect of different regularizers and their i...

0 Devis Tuia, et al. ∙

research

∙ 06/23/2016

Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions

In this paper, we tackle the question of discovering an effective set of...

0 Devis Tuia, et al. ∙

research

∙ 04/22/2016

Learning rotation invariant convolutional filters for texture classification

We present a method for learning discriminative filters using a shallow ...

0 Diego Marcos, et al. ∙

research

∙ 01/31/2016

Principal Polynomial Analysis

This paper presents a new framework for manifold learning based on a seq...

0 Valero Laparra, et al. ∙

research

∙ 04/09/2015

Kernel Manifold Alignment

We introduce a kernel method for manifold alignment (KEMA) and domain ad...

0 Devis Tuia, et al. ∙

Devis Tuia

Featured Co-authors