Remote sensing image building identification method and system based on multi-neural network integration, and electronic equipment

By constructing a multi-neural network integrated remote sensing image building recognition method, the problems of high computing power, large parameters, slow recognition and lack of rules in edge devices are solved, and efficient and accurate building recognition and safe flight strategies are achieved.

CN120689764APending Publication Date: 2025-09-23INST OF GEOGRAPHICAL SCI & NATURAL RESOURCE RES CAS
3 Cites 1 Cited by

Patent Information

Application Number
CN202510735486.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-04
Publication Date
2025-09-23

AI Technical Summary

Technical Problem

Existing remote sensing image building recognition models require high computing power and are not suitable for edge device deployment. They have large model parameters, slow recognition speed, poor regional information perception capabilities, and a lack of rule-based strategies, resulting in high potential risks for edge devices.

Method used

A primitive edge network consisting of a Mobilenet encoder, a Transformer encoder, a U-Net decoder, and the output of a segmentation head is constructed and trained on conventional and single-class building datasets. The model parameter package is stored on a cloud server, and the model is optimized based on the edge device positioning and regional information, and recognition is performed by matching spatial domain rules.

Benefits of technology

It reduces model parameters and computing power requirements, improves building recognition accuracy, implements adaptive matching and hard limits, and reduces potential risks of edge devices.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention belongs to the technical field of image recognition, and provides a remote sensing image building recognition method and system based on multi-neural network integration, and electronic equipment. The method comprises the steps of original edge network construction, two-class standard building data set construction, multi-class model parameter training, positioning information acquisition, remote sensing image acquisition, region related information extraction, main building type determination, airspace rule matching, parameter and rule lowering, model parameter updating and image recognition. According to the invention, the original edge network is constructed, so that the requirements on model parameters and computing power are reduced; through the trained multi-class model parameters, region related information extraction and main building type determination, adaptive matching of the model parameters according to different scene types is realized, the building identification accuracy is improved, and the volume of the edge model is reduced; through airspace rule matching, movement or flight of edge equipment is limited, and potential risks of personnel and buildings are reduced.
Need to check novelty before this filing date? Find Prior Art