Reliability evaluation of incomplete AIS trajectories

International audienceAutomatic Identification System (AIS) data are prone to alterations that impede signal storage, producing incomplete trajectories. Since trajectory analysis assumes complete AIS data sets, incomplete trajectories are discarded. Yet, those data sets contain proper values, which could be exploited. This paper describes an approach to estimate the degree of reliability assigned to missing segments of a vessel trajectory, depending on meaningful statistical variations of recorded and predicted vessel positions. The approach was tested on real AIS data of three vessels. Results suggest that reliability can be determined from vessel speed and heading variations

Segmentation 3D et analyse de bancs de poissons à partir d'une séquence d'images acquise par un sonar multi-faisceaux

Ce travail s'inscrit dans le cadre d'un projet dont l'objectif est l'analyse des ressources halieutiques à l'aide de séquences d'images acquises par un sonar multi-faisceaux. Nous présentons quelques méthodes de segmentation, d'extraction, de visualisation et d'analyse 3D des bancs de poissons et du fond marin présents dans les séquences. Les caractéristiques techniques du sonar et la résolution des images obtenues sont tout d'abord décrite. Ensuite, le volume des données est corrigé pour compenser le mouvement du bateau au cours de l'acquisition (tangage, roulis, pilonnement, cap et vitesse du bateau). Nous présentons également deux algorithmes de segmentation 3D pour l'extraction du fond marin et des bancs de poissons dans une séquence. Enfin, l'analyse des bancs de poissons extraits est réalisée grâce à quelques descripteurs 3D en vues d'études bio-statistiques sur les ressources halieutiques

Utilisation de méthodes basées sur la théorie des ensembles flous pour l'extraction de contours

International audienceUtilisation de méthodes basées sur la théorie des ensembles flous pour l'extraction de contour

Secured Electronic Patient Records Content Exploitation

International audienceThe increasing need for medical information applications to handle varied multimedia data through interoperable systems is continually hindered by incompatible limited platforms, with low or non-existent security. Using the workflow of an imaging service, this chapter describes the structure and protection strategy of a secured specialized electronic patient record which allows exchanging of multimedia medical data in a secured manner. An open multimedia standard adapted to patient record requirements has been applied, combined with security tools. Prospective application scenarios are identified, and the main issues of the approach are discussed

Data mining system applied in endoscopic image base

International audienceSince 1980, many hospital information systems (HIS) came into being. These HIS are at the origin of the storage of huge medical data. Data mining is a domain which presents the most powerful tools for the extraction of knowledge and for structuring them. The first intelligent systems or assistance systems for medical diagnosis are the case-base reasoning systems. In these systems, the data mining method was integrated to improve them and to fill some gaps. We present an application of data mining which is based on case-base reasoning. The characteristic of this application is building knowledge base without integrating expert knowledge and we use this knowledge base to retrieve casefrom case base

Suivi bilatéral des structures vasculaires dans les images d'angiographie et reconstruction 3-D des branches principales du réseau vasculaire coronarien à partir de deux projections angiographiques

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A new hybrid fusion hybrid method for diagnostic system

International audienceIn this work, we present a new fusion method based on fuzzy set theory. This method consists of combining several data and knowledge bases of diagnostic systems. It is characterized by a hybrid fusion, which combines base fusion of data and knowledge of the Case-Based Reasoning diagnostic systems. The fusion method relies on distortion measure of various diagnostic systems (of case and knowledge bases). This distortion measure is integrated into the diagnostic system in order to improve its performance. It is defined by confidence degrees associated to each parameter that composes the case and knowledge bases of diagnostic systems. The confidence degrees are then integrated into the diagnostic system procedure

Nouvelle méthode d'extraction de règles de classification multi-labels

International audienceNouvelle méthode d'extraction de règles de classification multi-label

Rule-based diagnostic system fusion

International audienceIn this work, we present a new fusion method that uses fuzzy set theory. This method is applied to the diagnostic system rule bases. It aims at combining all the rule bases into only one rule base and then taking into consideration the characteristics of this base. The fusion method is characterized by a hybrid fusion which combines rule fusion approach with knowledge fusion approach. Knowledge fusion relies on the distortion measure of various bases. This distortion measure is integrated into the rule fusion process in order to generate one rule base for improving the diagnostic system performance. It is defined as the confidence degrees associated to each rule base parameter. The confidence degrees are then integrated into prediction procedure of the new diagnostic system