Thales

Sispia

Safran Aircraft Engines

Snecma

Universite Dé Lorraine

Ion Berechet

Stefan Berechet

Gérard Berginc

Serge Daniel Le Gonidec

Dimitri Malikov

Gerard Berginc

Jean-Baptiste Bellet

A method for an object of interest in a degraded 2D digital image of the object is provided. The method includes the following steps: detecting, beforehand, the object of interest in a 2D digital image and assigning it a label; reconstructing a 3D volume of the object thus labeled from a plurality of available 2D digital images of the object of interest; storing, in a database, a record relating to the object thus reconstructed in 3D form and labeled; for each record thus stored, generating a new plurality of 2D digital images according to a plurality of viewing modes from the thus reconstructed 3D volume of each object; training a neural network on a learning set composed of an expanded set of 2D digital images thus generated and corresponding with the label of the object of interest to be recognized; from a degraded 2D digital image of the object of interest to be recognized; using the neural network thus trained to deliver as output the label of the object and a confidence index linked to the recognition of the object of interest.

Object recognition method with increased representativeness

An information processor system for monitoring a complex system and including a mechanism receiving at least one piece of event detection information associated with a detection time and a mechanism generating at least one remanent confidence level value that decreases over time starting from the detection time.

Information processor system for monitoring a complex system

A method for discriminating and identifying, by 3D imaging, an object in a complex scene comprises the following steps: generating a sequence of 2D MIP images of the object, from a 3D voxel volume of the complex scene, this volume visualized by an operator by using an iterative process of MIP type from a projection plane and an intensity threshold determined by the operator on each iteration, automatically extracting, from the sequence of images, coordinates of a reduced volume corresponding to the sequence of images, choosing one of the intensity thresholds used during the iterations, automatically extracting, from the 3D volume of the complex scene, from the coordinates and chosen intensity threshold, a reduced 3D volume containing the object, automatically generating, from the reduced volume, by intensity threshold optimization, an optimized intensity threshold and an optimized voxel volume, a color being associated with each intensity, identifying the object by visualization.

Method for discrimination and identification of objects of a scene by 3-D imaging

A data processor system for monitoring a complex system, the processor system configured to receive a plurality of pieces of state information and to merge at least the pieces of state information into a piece of failure information, at least one of the pieces of state information being associated with a confidence flag, and the piece of failure information also being associated with a confidence flag. The system performs the merging by implementing a fuzzy logic technique to produce the piece of failure information while taking account of the respective confidence flag of the pieces of state information and to produce the confidence flag associated with the failure information.

Information processing system and method for monitoring a complex system

A method for 3D reconstruction of an object based on back-scattered and sensed signals, including: generating, from the sensed signals, 3D points to which their back-scattering intensity is respectively assigned, which form a set A of reconstructed data, starting from A, extracting a set B of data, whose points are located within a volume containing the object, as a function of volume characteristics F, starting from B, extracting a set C of data characterizing the external surface of the object, the surface having regions with missing parts, depending on an extraction criterion, based on C, filling in the regions with missing parts by generation of a three-dimensional surface so as to obtain a set D of completed data of the object, without having to use an external database, and identifying the object based on D.

Method for 3D reconstruction of an object in a scene

A method for synthetic reconstruction of objects includes: extracting criteria from a knowledge base; extracting, from sensed signals filtered by the criteria, weak signals; extracting, from the weak signals, weak signals of interest; removing noise from and amplifying the weak signals of interest and obtaining useful weak signals; identifying useful direct information, from useful weak signals filtered by the criteria and supplying optimum criteria; reconstructing, using the useful direct information, information of interest; reconstructing, using the information of interest, useful information and supplying optimum criteria; reconstructing, based on the useful information, three-dimensional information, supplying a recognition state file and supplying the optimum criteria; and updating the criteria with the optimum criteria.

Growing community of inventors

Vincennes, France

Ion Berechet