Anomaly detection algorithm based on copying and pasting

A copy-and-paste and anomaly detection technology, which is applied in computing, program control design, computer components, etc., can solve problems such as lack of prior information, and achieve the effect of improving the insufficient definition of anomalies

Pending Publication Date: 2021-12-10
北京中科智眼科技有限公司
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Problems solved by technology

[0003] The original training mode of the industrial anomaly detection algorithm is the original image → network → reconstructed image. The existing technologies are all proposed based on the background of no abnormal data in the training set, which means that the

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  • Anomaly detection algorithm based on copying and pasting
  • Anomaly detection algorithm based on copying and pasting

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Embodiment Construction

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. The specific embodiments described here are only used to explain the present invention, not to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0041] The present invention provides such Figure 1-3 Example shown:

[0042] An anomaly detection algorithm based on copy and paste, including the following steps:

[0043] Step 1. Data preparation: Prepare a sufficient amount of PNG images with alpha channels;

[0044] Step 2. Feature extraction and reconstruction; first, input the ...

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Abstract

The invention discloses an anomaly detection algorithm based on copying and pasting. The algorithm comprises the four steps of data preparation, feature extraction and reconstruction, training based on a copying and pasting mode and anomaly scoring. The invention provides a novel training mode of an original image, copied and pasted exceptions, a network and a reconstructed image. The original reconstruction function is further upgraded, the original loss function only comprises L2 loss, and the proposed new reconstruction loss function enables the network to compare the similarity between the original image and the reconstructed image from multiple dimensions of brightness, contrast and structure by introducing an SSIM function; the prior art is put forward on the basis of the background that a training set has no abnormal data, which means that the prior art has the defect of lack of prior information, but copying and pasting learning can make up the defect. Firstly, data augmentation can be realized by using a copy-paste learning mode, the defect of scarcity of abnormal data in the prior art is made up, and the common problem of reconstruction error failure in a traditional pixel-level reconstruction model is improved.

Description

technical field [0001] The invention belongs to the technical field of anomaly detection algorithms, and in particular relates to an anomaly detection algorithm based on copy and paste. Background technique [0002] Industrial anomaly detection is often faced with the fact that normal patterns can be clearly defined, but potential anomalous patterns that may exist cannot be defined. Therefore, how to define and distinguish target samples has become a hot spot in academia and industry. Influenced by the field of deep learning, most of the solutions to anomaly detection problems currently focus on deep learning methods, for example: the reconstruction model in the form of an autoencoder, whose purpose is to learn the accurate data distribution of the target sample, and we will A new type of training mode introduces anomaly detection, the purpose of which is to randomly build anomalies to improve the robustness of the model, where copy and paste means random paste, that is, by...

Claims

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Application Information

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IPC IPC(8): G06F9/54G06K9/62G06N3/04G06N3/08
CPCG06F9/543G06N3/08G06N3/045G06F18/22
Inventor 齐志泉徐睿婕
Owner 北京中科智眼科技有限公司
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