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Devis Tuia

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Publications associées (151)

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

Devis Tuia, Frank Grégoire Jean de Morsier, Giona Matasci

2014

Hydrometeor classification from two-dimensional video disdrometer data

Devis Tuia, Alexis Berne, Marc Schneebeli Zeugin, Jacopo Grazioli, Samuel Monhart, Timothy Hugh Raupach

The first hydrometeor classification technique based on two-dimensional video disdrometer (2DVD) data is presented. The method provides an estimate of the dominant hydrometeor type falling over time intervals of 60 s during precipitation, using the statist ...

European Geosciences Union2014

Picture density in the space of geographic features: mapping landscape attractiveness

François Golay, Devis Tuia, Frank Grégoire Jean de Morsier, Timothée Produit

2014

Semisupervised Manifold Alignment of Multimodal Remote Sensing Images

Devis Tuia, Maxime Pierre Trolliet

We introduce a method for manifold alignment of different modalities (or domains) of remote sensing images. The problem is recurrent when a set of multitemporal, multisource, multisensor, and multiangular images is available. In these situations, images sh ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Principal Polynomial Analysis

Devis Tuia

This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of ma ...

World Scientific Publ Co Pte Ltd2014

Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM

Devis Tuia

Including spatial information is a key step for successful remote sensing image classification. In particular, when dealing with high spatial resolution, if local variability is strongly reduced by spatial filtering, the classification performance results ...

Ieee-Inst Electrical Electronics Engineers Inc2014

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

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

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

Advances in hyperspectral image classification

Devis Tuia

The technological evolution of optical sensors over the last few decades has provided remote sensing analysts with rich spatial, spectral, and temporal information. In particular, the increase in spectral resolution of hyperspectral images (HSIs) and infra ...

Institute of Electrical and Electronics Engineers2014

Multisource Clustering of Remote Sensing Images With Entropy-Based Dempster-Shafer Fusion

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

In this paper, we propose a strategy for fusing clustering maps obtained with different remote sensing sources. Dempster- Shafer (DS) Theory is a powerful fusion method that allows to combine classifications from different sources and handles ignorance, im ...

IEEE2013

Hydrometeor classification using clustering of polarimetric radar measurements

Devis Tuia, Alexis Berne, Jacopo Grazioli

2013

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

Semi-Supervised Novelty Detection using SVM entire solution path

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

Very often, the only reliable information available to perform change detection is the description of some unchanged regions. Since sometimes these regions do not contain all the relevant information to identify their counterpart (the changes), we consider ...

Institute of Electrical and Electronics Engineers2013

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Devis Tuia

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

Hydrometeor classification from two-dimensional video disdrometer data

Picture density in the space of geographic features: mapping landscape attractiveness

Semisupervised Manifold Alignment of Multimodal Remote Sensing Images

Principal Polynomial Analysis

Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM

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

Advances in hyperspectral image classification

Multisource Clustering of Remote Sensing Images With Entropy-Based Dempster-Shafer Fusion

Hydrometeor classification using clustering of polarimetric radar measurements

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

Semi-Supervised Novelty Detection using SVM entire solution path

Hydrometeor classification using data mining techniques and polarimetric radar observations

Investigating the feature extraction framework for domain adaptation in remote sensing image classification

Kernel sparse subspace clustering

Multisource alignment of image manifolds

Hyperspectral and LiDAR data fusion for high resolution urban land cover / land use classification

Create the relevant spatial filterbank in the hyperspectral jungle

Multi-view feature extraction for hyperspectral image classification

Domain adaptation with hidden Markov random fields