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1. WO2020159960 - GENERATING GROUND TRUTH FOR MACHINE LEARNING FROM TIME SERIES ELEMENTS

Publication Number WO/2020/159960
Publication Date 06.08.2020
International Application No. PCT/US2020/015371
International Filing Date 28.01.2020
IPC
G16Y 20/10 2020.1
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
YINFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS
20Information sensed or collected by the things
10relating to the environment, e.g. temperature; relating to location
CPC
G05D 1/0221
GPHYSICS
05CONTROLLING; REGULATING
DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
1Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
02Control of position or course in two dimensions
021specially adapted to land vehicles
0212with means for defining a desired trajectory
0221involving a learning process
G06K 9/6255
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
6255Determining representative reference patterns, e.g. averaging or distorting patterns; Generating dictionaries, e.g. user dictionaries
G06N 3/04
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
G06N 3/08
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
G06V 20/588
G16Y 20/10
GPHYSICS
16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
YINFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
20Information sensed or collected by the things
10relating to the environment, e.g. temperature; relating to location
Applicants
  • TESLA, INC. [US]/[US]
Inventors
  • ELLUSWAMY, Ashok Kumar
  • BAUCH, Matthew
  • PAYNE, Christopher
  • KARPATHY, Andrej
  • POLIN, Joseph
Agents
  • FULLER, Michael L.
Priority Data
16/265,72901.02.2019US
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) GENERATING GROUND TRUTH FOR MACHINE LEARNING FROM TIME SERIES ELEMENTS
(FR) GÉNÉRATION DE RÉALITÉ DE TERRAIN POUR APPRENTISSAGE MACHINE À PARTIR D'ÉLÉMENTS DE SÉRIES CHRONOLOGIQUES
Abstract
(EN) Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.
(FR) Des données de capteur, comprenant un groupe d'éléments de série chronologique, sont reçues. Un ensemble de données d'apprentissage est déterminé, notamment par détermination, pour au moins un élément de série chronologique sélectionné dans le groupe d'éléments de série chronologique, d'une réalité de terrain correspondante. La réalité de terrain correspondante est basée sur une pluralité d'éléments de série chronologique dans le groupe d'éléments de série chronologique. Un processeur est utilisé pour entraîner un modèle d'apprentissage machine à l'aide de l'ensemble de données d'apprentissage.
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