Éditeur(s) : HAL CCSD
Résumé : International audience
This work proposes an original approach using mutual information and Pareto curve jointly for feature selection. Mutual information is used to estimate dependency criterion between features and classes and redundancy criterion between features taken two by two. Unlike some studies, these criteria are used simultaneously to compute Pareto curve and determine the optimal feature sets. This approach is tested on more reference data. Several clustering algorithms are used to compute classification accuracy. The obtained results show the importance of our tools and its ability to select the best feature sets that give the better description.
GRETSI Proceedings
Bordeaux, France

hal-00602260
https://hal.archives-ouvertes.fr/hal-00602260

Éditeur(s) : HAL CCSD IEEE
Résumé : Object classification is a challenging task in computer vision. Many approaches have been proposed to extract meaningful descriptors from images and classifying them in a supervised learning framework. In this paper, we revisit the classic k-nearest neighbors (k-NN) classification rule, which has shown to be very effective when dealing with local image descriptors. However, k-NN still features some major drawbacks, mainly due to the uniform voting among the nearest prototypes in the feature space. In this paper, we propose a generalization of the classic k-NN rule in a supervised learning (boosting) framework. Namely, we redefine the voting rule as a strong classifier that linearly combines predictions from the k closest prototypes. To induce this classifier, we propose a novel learning algorithm, MLNN (Multiclass Leveraged Nearest Neighbors), which gives a simple procedure for performing prototype selection very efficiently. We tested our method on 12 categories of objects, and observed significant improvement over classic k-NN in terms of classification performances.
International Workshop on Image Analysis for Multimedia Interactive Services
Desenzano del Garda, Italy

hal-00481725
https://hal.archives-ouvertes.fr/hal-00481725
https://hal.archives-ouvertes.fr/hal-00481725/document
https://hal.archives-ouvertes.fr/hal-00481725/file/pbnn_wiamis_10.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
IAHR
La Haye, Netherlands

hal-01313382
https://hal.archives-ouvertes.fr/hal-01313382

Éditeur(s) : HAL CCSD
Résumé : International audience
IHMA
Lille, France

hal-01313395
https://hal.archives-ouvertes.fr/hal-01313395

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.
ISSN: 0098-3004

hal-01369822
https://hal.archives-ouvertes.fr/hal-01369822
https://hal.archives-ouvertes.fr/hal-01369822/document
https://hal.archives-ouvertes.fr/hal-01369822/file/CAGEO-D-13-00538R1_article.pdf
DOI : 10.1016/j.cageo.2014.08.013

Éditeur(s) : HAL CCSD
Résumé : International audience
Dans cet article, on utilise une méthode de segmentation appliquée à la reconnaissance de végétaux dans des images. La segmentation fournit des groupes de pixels, et nous proposons d'utiliser des opérateurs d'agrégation pour ordonner ces groupes afin d'améliorer les performances du système de reconnaissance. En particulier, on utilise un opérateur totalement renforcé appelé triple pi. Les premiers tests sont réalisés et montrent que l'utilisation du triple pi améliore les résultats pour la structuration des groupes de pixels.
7ème Atelier Fouille de Données Complexes dans un processus d'extraction de connaissances - Complexité liée aux données multiples
Hammamet, Tunisia

hal-00509725
https://hal.archives-ouvertes.fr/hal-00509725

Éditeur(s) : HAL CCSD Institute of Electrical and Electronics Engineers
Résumé : International audience
Tailoring nearest neighbors algorithms to boosting is an important problem. Recent papers study an approach, UNN, which provably minimizes particular convex surrogates under weak assumptions. However, numerical issues make it necessary to experimentally tweak parts of the UNN algorithm, at the possible expense of the algorithm's convergence and performance. In this paper, we propose a lightweight alternative algorithm optimizing proper scoring rules from a very broad set, and establish formal convergence rates under the boosting framework that surprisingly compete with those known for UNN. It is an adaptive Newton-Raphson algorithm, which belongs to the same lineage as the popular Gentle Adaboost. To the best of our knowledge, no such boosting-compliant convergence rates were previously known for these algorithms. We provide experiments on a dozen domains, including the challenging Caltech and SUN computer vision databases. They display that GNNB significantly outperforms UNN, both in terms of convergence rate and quality of the solution obtained, and GNNB provides a simple and efficient contender to techniques that can be used on very large domains, like stochastic gradient descent -- for which little is known to date. Experiments include a divide-and-conquer improvement of GNNB which exploits the link with proper scoring rules optimization.
ISSN: 0162-8828

hal-00958809
https://hal.archives-ouvertes.fr/hal-00958809
https://hal.archives-ouvertes.fr/hal-00958809/document
https://hal.archives-ouvertes.fr/hal-00958809/file/PAMI.pdf
DOI : 10.1109/TPAMI.2014.2307877

Éditeur(s) : HAL CCSD
Résumé : National audience
EIAH Proceedings

hal-00634758
https://hal.archives-ouvertes.fr/hal-00634758

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper deals with hybrid optimization take different methods to solve a complex problem. As if the choice of concerning methods is important, the way to combine them is determinant for an ef cient search. The article deals with cooperation strategy between the different layers of an hybrid optimization algorithm. We describ the way it is articulated for an Satellite Constellation Optimization problem. This cooperation allows a dynamical adaptation of the optimization algorithm parameters according to the mutual advance of each search
Journal Européen des Systèmes Avancés

hal-00602267
https://hal.archives-ouvertes.fr/hal-00602267

Éditeur(s) : HAL CCSD
Résumé : National audience
Conférence du Centre d'Etudes Supérieures de Civilisation Médiévale (CESCM)
Poitiers, France

hal-00694124
https://hal.archives-ouvertes.fr/hal-00694124

Éditeur(s) : HAL CCSD IOP Publishing
Résumé : International audience
Based on the very recent work by Censor and Segal (2009 J. Convex Anal. 16 587-600) and inspired by Xu (2006 Inverse Problems 22 2021-34) and Yang (2004 Inverse Problems 20 1261-6), we investigate an algorithm for solving the split common fixed-point problem for the class of demicontractive operators in a Hilbert space. Our results improve and/or develop previously discussed feasibility problems and related algorithms. It is worth mentioning that the convex feasibility formalism is at the core of the modeling of many inverse problems and has been used to model significant real-world problems, for instance, in sensor networks, in radiation therapy treatment planning, in computerized tomography and data compression, see Censor et al (2006 Phys. Med. Biol. 51 2353-65) and Combettes (1996 Adv. Imaging Electron. Phys. 95 155-270) and references therein.
ISSN: 0266-5611

hal-00778174
https://hal.univ-antilles.fr/hal-00778174
DOI : 10.1088/0266-5611/26/5/055007

Éditeur(s) : HAL CCSD
Résumé : International audience
ICECS Proceedings
Dubai, United Arab Emirates

hal-00509490
https://hal.archives-ouvertes.fr/hal-00509490

Éditeur(s) : HAL CCSD
Observation des Côtes et des Océans : Senseurs et Systèmes, OCOSS 2010
Brest, France

inria-00564722
https://hal.inria.fr/inria-00564722

Éditeur(s) : HAL CCSD
Résumé : International audience
IGARSS
Melbourne, Australia

hal-01313386
https://hal.archives-ouvertes.fr/hal-01313386

Éditeur(s) : HAL CCSD
Résumé : International audience
SELPER
Cayenne, French Guiana

hal-01313391
https://hal.archives-ouvertes.fr/hal-01313391

Éditeur(s) : HAL CCSD
Résumé : International audience
The development of the mine, gas and oil extraction in the Eastern Venezuela (Oriente and Guayana regions) and the Far Eastern (Oriental Siberia) is characterized by the emergence of pioneer small and medium cities during the last fifty years and an emerging process of metropolisation since 2000 (Yakutsk, Ciudad Guayana). In Eastern Venezuela, the urbanization is partially planned, generally “spontaneous”. In Yakutia, dynamics of urbanization is planned. In the both cases, urban dynamics is driven by the exploitation of the natural resources and the immigration. With the collapse of the Soviet Union, some mining towns disappeared in the 1990 and 2000. Since the beginning of the 2010’s mining urban regions are under a double process of territorial integration with Russian Europe and Asia. In Venezuela, small and medium sized cities are growing with the emergence of new mining territories and the exploitation of the Orinoco Belt (extra heavy oil). This article analyses the main territorial dynamics of these small and medium sized cities.
Digital Cities and Spatial Justice

ISBN : 978-84-697-4984-5
hal-01584550
https://hal-amu.archives-ouvertes.fr/hal-01584550

Éditeur(s) : HAL CCSD
Résumé : International audience
Half away between edge detection and object recognition this study aim to characterize singularities in order to guide this two phases. The caracterization is obtained with a generalization of the Lipschitz exponents .for complex structures. This new characterization is called " maxima chain " and integrates the notion of value and spatial repartition of the maxima. The maxima chains are obtained with a multiscale decomposition using a Diadic Discrete Wavelet Transform (DDWT). We use the maxima of the gradient image computed with the wavelet details. The local maxima detect the position of irregular structures (edges) in the image (Canny algorithm). Then we characterize each maxima using their evolution across the different scales. A classification is made using the maxima chains. We integrate the classification to eliminate unwanted maxima (from noise or other objects) to drive the search of closed contours. In fact, there is a totally different signature from one maxima to another depending on the parameters of the objects : nature, shape, size, gray scale, texture, ...
RFIA Proceedings
Toulouse, France

hal-00602265
https://hal.archives-ouvertes.fr/hal-00602265

Éditeur(s) : HAL CCSD
Résumé : International audience
Les écosystèmes forestiers des Caraïbes

hal-00634756
https://hal.archives-ouvertes.fr/hal-00634756

Éditeur(s) : HAL CCSD
Résumé : International audience
Graphomotor control constitutes a condition to the mastery of literacy and more widely to successful school apprenticeship. The Guadeloupian context is marked by significant rates of early school leaving and illiteracy. In such context, our research is concerned with two questions: “Does graphomotor training can help since kindergarten to strengthen graphomotor performances and the progression of literacy?” and “Which methodological approach can help to characterize the impact of graphomotor training?” By using online acquisition devices, we have tried to characterize the graphomotor skills for 132 pupils. These 3 to 5 years old children were submitted to 3 methods of graphomotor training. One of the methods that suppose family involvement, includes activities inspired by kid’s early scribbles. We considered the statistical analysis of the blind feedbacks of the teachers, of the features provided by the visuo-spatial processing of handwritten productions and of features provided by the sigma-lognormal modeling of the pupils’ movements. The results of this multimodal study show an increase in graphomotor control and in interest for drawing and handwriting tasks. The implication of these preliminary results on the pedagogical and co-educative choices is discussed.
Yves Mazabraud, Thomas Forissier, Alain Pietrus, Olivier Gros, Claire Anjou. CARIBBEAN ACADEMY OF SCIENCES 20 th GENERAL ASSEMBLY AND BIENNAL MEETING: Planning and Abstracts book. Nov 2016, Dehaies, Guadeloupe. 2016.
Deshaies, Guadeloupe

hal-01516420
https://hal.archives-ouvertes.fr/hal-01516420

Éditeur(s) : HAL CCSD
Résumé : National audience
Journées d'Orthopédie, Obésité/biodiversité et Orthopédie
Baie-Mahault, Guadeloupe

hal-00762796
https://hal.archives-ouvertes.fr/hal-00762796