Remote sensing image target detection method and system based on semi-supervised iterative learning

Abstract

The invention provides a remote sensing image target detection method and system based on semi-supervised iterative learning, and the method comprises the steps: collecting a remote sensing image target detection data set which comprises a label data set and a mass label-free data set; training a target detector model based on the labeled data set, and obtaining a trained initial target detector model; dividing the massive label-free data set into a plurality of label-free data subsets; and performing iterative optimization training on the initial target detector model based on the labeled data set and the plurality of unlabeled data subsets to obtain a final target detector model. According to the invention, a small amount of tagged remote sensing image data is used, and the target detection precision is greatly improved and the manual tagging cost is reduced under the combined auxiliary optimization of massive non-tagged data.

Description

technical field [0001] The present invention relates to the field of remote sensing image target detection, and more specifically, to a remote sensing image target detection method and system based on semi-supervised iterative learning. Background technique [0002] With the rapid development of social economy and computer technology, deep learning is gradually applied in various fields. In computer vision methods, there are mainly many tasks such as target detection, image classification, and image understanding. Based on the method of deep learning, the training model requires a large amount of labeled data support. Traditionally, the fully supervised learning method is used, that is, only labeled data is used, and unlabeled data is directly discarded, which will cause a large degree of waste of data. Under normal circumstances, unlabeled data is easy to obtain, and with the continuous development of technology, any image data in the database has shown exponential growth, ...

AI Technical Summary

Problems solved by technology

[0003] The remote sensing image target detection task is a relatively difficult task. The remote sensing image is a top view, with a complex background, dense objects and arbitrary directions in the image. Usually, the resolution of the remote sensing image is very large, so when labeling the image Time to further increase the cost of labeling, need to consume more manpower and material resources

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