Remote sensing image scene classification method based on attribute guidance
By adopting an attribute-based guidance method in remote sensing image scene classification technology, generating attribute nouns and enriching language information representations, the problem of low classification accuracy caused by monotony in the prior art is solved, and higher consistency and accuracy are achieved.
CN119723183APending Publication Date: 2025-03-28INNER MONGOLIA UNIV OF TECH
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Patent Information
- Application Number
- CN202411788019.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-06
- Publication Date
- 2025-03-28
AI Technical Summary
Technical Problem
The existing remote sensing image scene classification technology cannot comprehensively summarize image features due to monotonous language information, which affects the classification results.
Method used
The attribute guidance method is adopted to generate attribute nouns by extracting and generating attribute nouns from the attribute features of the image, and using these attribute nouns to enrich the language information representation, thereby improving the accuracy of language supervision and scene classification.
Benefits of technology
By integrating the distinguishable attribute characteristics of the image, the consistency between language information and image content is significantly improved, and the accuracy of scene classification is improved.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides a remote sensing image scene classification method based on attribute guidance, and relates to the technical field of remote sensing image processing, and the method comprises the following steps: obtaining a to-be-classified remote sensing image and a corresponding scene class text; constructing and training a scene classification network; processing the to-be-classified remote sensing image and the scene category text by using the trained scene classification network to obtain a scene classification result corresponding to the to-be-classified remote sensing image; according to the method, the attribute features of the remote sensing image are utilized, so that the language information can contain each part of the image with differentiated content, and the consistency between the language information and the image content is improved.
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