Invention Application
- Patent Title: LEARNING METHOD FOR A NEURAL NETWORK EMBEDDED IN AN AIRCRAFT FOR ASSISTING IN THE LANDING OF SAID AIRCRAFT AND SERVER FOR IMPLEMENTING SUCH A METHOD
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Application No.: US16691031Application Date: 2019-11-21
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Publication No.: US20200168111A1Publication Date: 2020-05-28
- Inventor: Yoan VEYRAC , Patrick GARREC , Pascal CORNIC
- Applicant: THALES
- Priority: com.zzzhc.datahub.patent.etl.us.BibliographicData$PriorityClaim@3252ba10
- Main IPC: G08G5/02
- IPC: G08G5/02 ; G05D1/10 ; G06N3/08 ; G06T17/05

Abstract:
The method uses a fleet of aircraft being equipped with at least one radar sensor, it includes at least: a step of collective collection of radar images by a set of aircraft (A1, . . . AN) of the fleet, the radar images being obtained by the radar sensors of the aircraft (A1, . . . AN) in nominal landing phases on the runway, a step wherein each image collected by an aircraft is labelled with at least information on the position of the runway relative to the aircraft, the labelled image being sent to a shared database and stored in the database; a step of learning by a neural network of the runway from the labelled images stored in the shared database, at the end of the step the neural network being trained; a step of sending of the trained neural network to at least one of the aircraft (A1).
Information query
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