Article detection method and device, electronic equipment and storage medium

CN120258828APending Publication Date: 2025-07-04NETEASE (HANGZHOU) NETWORK CO LTD
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Patent Information

Application Number
CN202410014083.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-01-04
Publication Date
2025-07-04

AI Technical Summary

Technical Problem

Existing image feature matching techniques are susceptible to interference in insufficient light or complex backgrounds, resulting in inaccurate object detection results.

Method used

Through the pre-trained neural network model, determine the category of items corresponding to the image to be inspected, set the network layer parameters of the neural network model, perform feature extraction and dimensionality reduction processing, and obtain the feature fingerprint of the item to improve detection accuracy.

Benefits of technology

It improves the accuracy of item detection, can accurately identify the authenticity of items in complex environments, adapt to the detection of different categories of items, and has strong scalability and adaptability.

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Abstract

The invention provides an article detection method and device, electronic equipment and a storage medium. The method comprises the following steps: determining the category of a to-be-detected article corresponding to a to-be-detected image; setting parameters of each network layer in the neural network model according to the category of the to-be-detected article; inputting a to-be-detected image into the neural network model for feature extraction to obtain a to-be-detected feature vector of the to-be-detected image; performing dimension reduction processing on the to-be-detected feature vector to obtain a to-be-detected feature fingerprint of the to-be-detected image; and determining the authenticity of the to-be-detected article according to the to-be-detected feature fingerprint. According to the technology, the influence of interference factors on the object detection result in the image feature matching process is relieved, and the object detection accuracy is improved.
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