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Remote sensing image small sample target detection method based on prototype convolutional neural network

A convolutional neural network, target detection technology, applied in remote sensing image small sample target detection, remote sensing image target detection field, can solve difficult remote sensing images and other problems, achieve high detection accuracy, save memory, and good robustness.

Pending Publication Date: 2021-05-28
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

The existing small sample target detection methods are difficult to be directly applied to remote sensing images

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  • Remote sensing image small sample target detection method based on prototype convolutional neural network
  • Remote sensing image small sample target detection method based on prototype convolutional neural network
  • Remote sensing image small sample target detection method based on prototype convolutional neural network

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Embodiment Construction

[0022] The present invention will be further described below in conjunction with the accompanying drawings and embodiments, and the present invention includes but not limited to the following embodiments.

[0023]The hardware environment used for implementation is: Intel(R) Core(TM) i3-8100 CPU computer, 8.0GB memory, and the running software environment is: Ubuntu16.04.5LTS and Pycharm2018. This experiment uses the large-scale remote sensing image public database DIOR Dataset, which has a total of 23463 images, of which 5862 images are divided into the training set, 5863 images are divided into the verification set, and the remaining 11738 images are divided into the test set. Covers 20 common remote sensing image targets. Each category contains approximately 1200 images with an image size of 800 × 800 pixels and a spatial resolution ranging from 0.5 m / pixel to 30 m / pixel. In order to verify the effectiveness of the proposed scheme above, baseball fields, basketball courts, ...

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Abstract

The invention provides a remote sensing image small sample target detection method based on a prototype convolutional neural network. A target detection network mainly comprising a feature extraction and category prototype acquisition module, a prototype guidance RPN module, a redirection feature map module and a detector module is constructed, network model basic learning is performed on a base class data set containing a large number of labeled samples, then a network model is finely adjusted on a balanced sub-data set, and finally, post-processing operations such as non-maximum suppression and the like are performed to realize multi-class target detection of the small sample remote sensing image. According to the method, different types of targets can be rapidly and accurately detected from the optical remote sensing image with the complex background by using a small amount of new class annotation data, and the method has relatively high detection precision and relatively high detection speed.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a small sample object detection method of remote sensing images based on a prototype convolutional neural network, which can be applied to remote sensing image object detection in the case of small samples with very few labeled sample data. Background technique [0002] With the continuous development of satellite remote sensing technology, the acquisition of massive remote sensing images has become easier and easier. However, the labeling of remote sensing images requires a lot of manpower and financial resources. In addition, some categories of objects are relatively rare, and there is a problem that data is difficult to obtain. Therefore, how to use a small number of labeled samples to realize target detection in remote sensing images has become one of the problems to be solved urgently. [0003] The existing small sample target detection ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06V20/13G06V10/25G06V10/462G06V2201/07G06F18/24
Inventor 程塨施佩珍闫博唯姚西文韩军伟郭雷
Owner NORTHWESTERN POLYTECHNICAL UNIV
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