Frank Grégoire Jean de Morsier

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The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...

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 ...

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 ...

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 ...

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 ...

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 ...

Frank Grégoire Jean de Morsier

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Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Unsupervised Change Detection via Hierarchical Support Vector Clustering

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

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

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

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

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

Hierarchical sparse representation for dictionary-based classification of hyperspectral images

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