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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...
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09/01/2023
Time Series Analysis of Urban Liveability
In this paper we explore deep learning models to monitor longitudinal li...
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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...
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05/15/2023
Artificial intelligence to advance Earth observation: a perspective
Earth observation (EO) is a prime instrument for monitoring land and oce...
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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...
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11/01/2022
Geo-Information Harvesting from Social Media Data
As unconventional sources of geo-information, massive imagery and text m...
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12/21/2021
Deep Learning and Earth Observation to Support the Sustainable Development Goals
The synergistic combination of deep learning models and Earth observatio...
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10/25/2021
Seeing biodiversity: perspectives in machine learning for wildlife conservation
Data acquisition in animal ecology is rapidly accelerating due to inexpe...
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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...
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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...
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07/29/2021
Mapping Vulnerable Populations with AI
Humanitarian actions require accurate information to efficiently delegat...
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04/15/2021
Semisupervised Manifold Alignment of Multimodal Remote Sensing Images
We introduce a method for manifold alignment of different modalities (or...
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04/15/2021
Learning User's confidence for active learning
In this paper, we study the applicability of active learning in operativ...
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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...
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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...
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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...
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01/20/2021
Self-supervised pre-training enhances change detection in Sentinel-2 imagery
While annotated images for change detection using satellite imagery are ...
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01/10/2021
Semantic Segmentation of Remote Sensing Images with Sparse Annotations
Training Convolutional Neural Networks (CNNs) for very high resolution i...
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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...
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09/18/2020
Contextual Semantic Interpretability
Convolutional neural networks (CNN) are known to learn an image represen...
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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...
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07/13/2020
OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing
OpenStreetMap (OSM) is a community-based, freely available, editable map...
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04/24/2020
Detecting Unsigned Physical Road Incidents from Driver-View Images
Safety on roads is of uttermost importance, especially in the context of...
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03/16/2020
RSVQA: Visual Question Answering for Remote Sensing Data
This paper introduces the task of visual question answering for remote s...
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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...
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07/23/2019
Adaptive Compression-based Lifelong Learning
The problem of a deep learning model losing performance on a previously ...
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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...
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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...
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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...
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01/24/2019
Correcting rural building annotations in OpenStreetMap using convolutional neural networks
Rural building mapping is paramount to support demographic studies and p...
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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 ...
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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...
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07/31/2018
Scale equivariance in CNNs with vector fields
We study the effect of injecting local scale equivariance into Convoluti...
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07/25/2018
Change Detection between Multimodal Remote Sensing Data Using Siamese CNN
Detecting topographic changes in the urban environment has always been a...
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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...
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05/17/2018
DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images
We present the DeepGlobe 2018 Satellite Image Understanding Challenge, w...
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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...
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03/16/2018
Learning deep structured active contours end-to-end
The world is covered with millions of buildings, and precisely knowing e...
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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...
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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...
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10/11/2017
Deep learning in remote sensing: a review
Standing at the paradigm shift towards data-intensive science, machine l...
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09/06/2017
Detecting animals in African Savanna with UAVs and the crowds
Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife mon...
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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...
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12/29/2016
Rotation equivariant vector field networks
In many computer vision tasks, we expect a particular behavior of the ou...
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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...
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06/23/2016
Non-convex regularization in remote sensing
In this paper, we study the effect of different regularizers and their i...
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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...
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04/22/2016
Learning rotation invariant convolutional filters for texture classification
We present a method for learning discriminative filters using a shallow ...
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01/31/2016
Principal Polynomial Analysis
This paper presents a new framework for manifold learning based on a seq...
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04/09/2015