Semi-supervised building change detection method and system based on CutMix-ResNet

Abstract

The invention discloses a semi-supervised building change detection method and system based on CutMix-ResNet. A remote sensing data set is divided into a labeled training data set and an unlabeled test data set; performing data preprocessing on the training data set; training a region-level teacher model and a sample-level teacher model by using an enhanced data set obtained by performing CutMix on the training data set; and jointly training a student model by using the two teacher models and a small amount of labeled data sets. According to the method, the original label data set is subjected to data enhancement by adopting the CutMix technology, and the respective self-supervision loss and the mutual cross pseudo-supervision loss of the two teacher models are optimized, so that the co-trained student models are more robust and complete, the generalization performance and the accuracy of the change detection model are improved, and the method can be used for change detection of remote sensing data.

Description

technical field [0001] The invention belongs to the technical field of change detection, and in particular relates to a semi-supervised building change detection method and system based on CutMix-ResNet. Background technique [0002] With the accelerated development of urbanization in my country, the scale of urbanization and construction land is constantly expanding, and the land census of construction land is becoming more and more important. However, with the continuous development of my country's economy, the method of using a large number of human resources for census is limited by low efficiency and high cost, and it is difficult to meet the needs of practical applications; therefore, it is very important to quickly and accurately find information on land cover changes. [0003] Building change detection aims to extract building change information through two dual-temporal remote sensing data through a variety of image processing and pattern recognition methods, and qu...

AI Technical Summary

Problems solved by technology

[0009] The technical problem to be solved by the present invention is to provide a semi-supervised building change detection method and system based on CutMix-ResNet for the deficiencies in the above-mentioned prior art, using a ResNet-based teacher-student (teacher-student) model and CutMix The technology judges the changes of surface buildings, improves the generalization performance and accuracy of the change detection model, and solves the problem that the existing deep learning change detection technology requires a large amount of supervision information but is limited by the high cost of human labeling

Images