Search results for "Pattern recognition"

Image classification based on 2D feature motifs

2013

The classification of raw data often involves the problem of selecting the appropriate set of features to represent the input data. In general, various features can be extracted from the input dataset, but only some of them are actually relevant for the classification process. Since relevant features are often unknown in real-world problems, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the candidate feature set. In this paper, we study the capability of a special class of motifs previously introduced in the literature, i.e. 2D irredundant motifs, when they are exploited as feat…

Noisy Channel in Language-Pair Phenomena Identification

2014

Perception of pathogenic or beneficial bacteria and their evasion of host immunity: pattern recognition receptors in the frontline

2015

International audience; Plants are continuously monitoring the presence of microorganisms to establish an adapted response. Plants commonly use pattern recognition receptors (PRRs) to perceive microbe- or pathogen-associated molecular patterns (MAMPs/PAMPs) which are microorganism molecular signatures. Located at the plant plasma membrane, the PRRs are generally receptor-like kinases (RLKs) or receptor-like proteins (RLPs). MAMP detection will lead to the establishment of a plant defense program called MAMP-triggered immunity (MTI). In this review, we overview the RLKs and RLPs that assure early recognition and control of pathogenic or beneficial bacteria. We also highlight the crucial func…

Active lighting applied to three-dimensional reconstruction of specular metallic surfaces by polarization imaging

2006

International audience; In the field of industrial vision, the three-dimensional inspection of highly reflective metallic objects is still a delicate task. We deal with a new automated three-dimensional inspection system based on polarization analysis. We first present an extension of the shape-from-polarization method for dielectric surfaces to metallic surfaces. Then, we describe what we believe to be a new way of solving the ambiguity concerning the normal orientation with an active lighting system. Finally, applications to shape-defect detection are discussed, and the efficiency of the system to discriminate defects on specular metallic objects made by stamping and polishing is presente…

Optimal Resource Allocation in Multi-Hop Networks: Contention vs. Scheduling

2014

CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance) is actually the most used method in ad-hoc networks for transmitting on a contending medium, even if it shows poor performance in presence of hidden nodes. To increase performance, we propose an algorithm that combines CSMA and TDMA (Time Division Multiple Access) approaches. The adopted solution consists of grouping contending nodes in non-interfering subsets and granting a different numbers of time slots to different groups, while using the CSMA to manage medium access among nodes belonging to the same subset. An optimization procedure to assign the time slots to each subset of nodes and to find an equilibrium between contention …

Contributions à l’imagerie polarimétrique et à ses applications en vision pour la robotique

2019

Ce mémoire présente le bilan de l'ensemble de mes travaux de recherche effectués de septembre 2006 à juin 2019 au sein de l'équipe Creusotine du laboratoire Le2i devenue équipe Vibot ERL CNRS 6000 depuis janvier 2018. Les principales activités de recherche que j'ai menées au cours de ces 10 dernières années autour de l'imagerie polarimétrique, de la vision omnidirectionnelle et de leurs applications en vision pour la robotique seront particulièrement détaillées dans ce document. Elles seront présentées selon deux grandes parties : la première concernera plutôt l'aspect mise en œuvre et calibrage des caméras et la seconde se concentrera sur les applications potentielles en vision pour la rob…

Contributions à l'analyse et à l'interprétation des images : Extraction et représentation de caractéristiques

2016

Ce mémoire, rédigé en vue de l'obtention de l'Habilitation à Diriger des Recherches (HDR), offre un aperçu des travaux de recherche et d’encadrement que j’ai pu mener depuis l'obtention de mon doctorat. Il montre la diversité des champs d’application et de recherche (en vision et en imagerie médicale) que j’ai pu couvrir , ainsi que mon implication dans l’encadrement doctoral.Mes activités de recherche se divisent en deux grandes parties. D'une part, l'analyse de scènes dynamiques, à savoir la détection de regions d'intérêt dans des séquences d'images, pour réduire la taile des données à traiter, et la détection et le suivi d'objets mobiles à l'aide de caméras de diverses natures (perspecti…

Visual saliency by keypoints distribution analysis

2011

In this paper we introduce a new method for Visual Saliency detection. The goal of our method is to emphasize regions that show rare visual aspects in comparison with those showing frequent ones. We propose a bottom up approach that performs a new technique based on low level image features (texture) analysis. More precisely, we use SIFT Density Maps (SDM), to study the distribution of keypoints into the image with different scales of observation, and its relationship with real fixation points. The hypothesis is that the image regions that show a larger distance from the mode (most frequent value) of the keypoints distribution over all the image are the same that better capture our visual a…

Automated Detection of Microaneurysms Using Scale-Adapted Blob Analysis and Semi-Supervised Learning

2014

International audience; Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are then introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier to detect true MAs. The developed system is built using only…

Some Investigations on Similarity Measures Based on Absent Words

2019

In this paper we investigate similarity measures based on minimal absent words, introduced by Chairungsee and Crochemore in [1]. They make use of a length-weighted index on a sample set corresponding to the symmetric difference M(x)ΔM(y) of the minimal absent words M(x) and M(y) of two sequences x and y, respectively. We first propose a variant of this measure by choosing as a sample set a proper subset (x, y) of M(x)ΔM(y), which appears to be more appropriate for distinguishing x and y. From the algebraic point of view, we prove that (x, y) is the base of the ideal generated by M(x)ΔM(y). We then remark that such measures are able to recognize whether the sequences x and y share a common s…