Method and system for detecting drift in image streams
AssigneeCapital One Services, LLC
InventorsKeegan Hines, Christopher Bayan Bruss
Life of this patent
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Abstract
Methods and systems disclosed herein may quantify a representation of a type of input an image analysis system should expect. The image analysis system may be trained on the type of input the image analysis system should expect using a first image stream. A first model of the type of input that the image analysis system should expect may be built from the first image stream. After the first model is built, a second image, or a second image stream, may be compared to the first model to determine a difference between the second image, or second image stream, and the first image stream. When the difference is greater than or equal to a threshold, a drift may be detected and steps may be taken to determine the cause of the drift.
Claims24
A method comprising:
- building, by a first device, a first model based on a first stream, wherein the first model represents a first probability distribution of a first plurality of features appearing in the first stream;
- building, by the first device, a second model based on a second stream, wherein the second model represents a second probability distribution of a second plurality of features appearing in the second stream;
- comparing the second model to the first model to determine a difference between the second stream and the first stream;
- and
- indicating that the second stream is significantly different from the first stream based on the difference being greater than or equal to a threshold, wherein significantly different indicates that the second stream is outside an accepted range of tolerance.
A computing device comprising:
- one or more processors;
- and
- memory storing instructions that, when executed by the one or more processors, cause the computing device to:
- build a first model based on a first stream, wherein the first model represents a first probability distribution of a first plurality of features appearing in the first stream;
- build a second model based on a second stream, wherein the second model represents a second probability distribution of a second plurality of features appearing in the second stream;
- compare the second model to the first model to determine a difference between the second stream and the first stream;
- and
- indicate that the second stream is significantly different from the first stream when the difference is greater than or equal to a threshold, wherein significantly different indicates that the second stream is outside an accepted range of tolerance.
A non-transitory computer-readable medium storing instructions that, when executed, cause a computing device to:
- build a first model based on a first stream, wherein the first model represents a first probability distribution of a first plurality of features appearing in the first stream;
- build a second model based on a second stream, wherein the second model represents a second probability distribution of a second plurality of features appearing in the second stream;
- compare the second model to the first model to determine a difference between the second stream and the first stream;
- and
- indicate that the second stream is significantly different from the first stream when the difference is greater than or equal to a threshold, wherein significantly different indicates that the second stream is outside an accepted range of tolerance.
Dependencies are inferred from the claim text.