Samsung patents method to train AI models using self-checked data
Samsung describes a technique for improving neural networks by having the model label new data and check its own confidence. The system keeps only the labels the model is highly sure about, creates variations of those examples, and uses them to retrain the network.
In the filing’s own words
The present disclosure relates to neural network training. The neural network training relates to a training method, a training device, and a system including the neural network. The neural network training includes extracting annotation data and first reliability values for first data using a neural network trained based on training data, selecting second data from among the first data based on the second data having second reliability values greater than or equal to a threshold value, expanding the training data based on the second data, and retraining the neural network based on the expanded training data.
What exactly they claim (claim 1)
1. A neural network training method comprising: providing a first training set comprising annotated training data; training a neural network in a first stage using the first training set; applying the trained neural network to unannotated data to obtain annotated data and reliability values for labels corresponding to the annotated data; selecting, as reference data, a piece of the annotated data having a first reliability value for its label that is greater than or equal to a threshold value; generating a plurality of transformed versions of the reference data by transforming the reference data; obtaining a reliability value for a corresponding label of each transformed version of the reference data; identifying two or more transformed versions of the reference data each having a second reliability value that is greater than or equal to a predefined reference value; selecting, at least two transformed versions of the reference data from the two or more transformed versions of the reference data; creating a second training set including the first training set and the at least two transformed versions of the reference data; and retraining the neural network in a second stage based on the second training set, wherein the at least two transformed versions of the reference data include a first number of transformed versions at a first reliability range and a second number of transformed versions at a second reliability range, wherein the first number is different from the second number.
Facts
- Company
- Samsung (SAMSUNG ELECTRONICS CO., LTD.)
- Official title
- Method and device for training neural network
- Patent number
- US12737607B2
- Application number
- 17033088
- Filed
- Sep 25, 2020
- Granted
- Sep 15, 2026
- Inventors
- 5
- Claims
- 16
Classified under
G06N 3/08 Physics & computingG06N 3/04 Physics & computingMore from Samsung in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.