FIELD: data processing.
SUBSTANCE: group of inventions relates to a method and a computer apparatus for forming training data for re-training a neural network for detecting objects. In order to form training data, a first digital image is introduced into the neural network (object detecting Neural Network, ODNN), constituting a digital signal of the detected object at a first moment of time, and a second digital image at a second moment of time after the first moment of time, said images are compared in order to determine the degree of similarity. If the degree of similarity is below the predetermined threshold value, the first or the second image is used to generate a human-evaluated label indicating the real part of the first or second image, and the ODNN network is re-trained.
EFFECT: object detection network ODNN is re-trained.
32 cl, 7 dwg
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|
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|
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METHOD AND SYSTEM FOR DETERMINING TRAJECTORY OF AUTONOMOUS VEHICLE | 2023 |
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METHOD AND SERVER FOR TEACHING A NEURAL NETWORK TO FORM A TEXT OUTPUT SEQUENCE | 2020 |
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METHOD AND SYSTEM FOR CHECKING MEDIA CONTENT | 2022 |
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METHOD AND SYSTEM FOR GENERATING TRAINING DATA FOR MACHINE LEARNING ALGORITHM | 2021 |
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METHOD AND SYSTEM FOR CLASSIFYING AN ELECTRONIC DEVICE USER | 2021 |
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METHOD, EQUIPMENT AND ELECTRONIC DEVICE FOR DETECTING A FACE VITALITY | 2018 |
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RU2714096C1 |
METHOD AND SYSTEM FOR TRAINING MACHINE LEARNING ALGORITHM FOR DETECTING OBJECTS AT A DISTANCE | 2020 |
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RU2775817C2 |
Authors
Dates
2021-12-28—Published
2020-04-10—Filed