A remote sensing image target detection method based on deep learning

A remote sensing image and target detection technology, applied in the field of panchromatic sharpening processing and target detection, can solve complex, time-consuming, difficult to learn classification models and other problems, achieve high spatial resolution, rich spectral information, time and The effect of low computational redundancy

Active Publication Date: 2021-08-10
TIANJIN UNIV
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Problems solved by technology

[0008] However, the above requirements are undoubtedly complex and time-consuming, and strongly depend on professional knowledge and the characteristics of the data itself. In addition, it is difficult to learn an effective classification model from large-scale data to fully exploit the interaction between large-scale data. associate

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  • A remote sensing image target detection method based on deep learning
  • A remote sensing image target detection method based on deep learning
  • A remote sensing image target detection method based on deep learning

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Embodiment Construction

[0023] In order to make the technical solution of the present invention clearer, the specific implementation manners of the present invention will be further described below. Such as figure 1 Shown, the present invention is concretely realized by the following steps:

[0024] 1. Construct a large-scale remote sensing image dataset

[0025] The present invention selects remote sensing image collections such as SpaceNet on AWS, NWPU VHR-10, and US Geological Survey USGS published on the Internet to construct a data set for detection tasks.

[0026] The NWPU VHR-10 dataset is a publicly available ten-category geospatial object detection dataset. These ten categories of items are aircraft, ships, oil storage tanks, ports and bridges, etc., including high-resolution images and label files of objects in the pictures and their annotations.

[0027] SpaceNet is a large-scale remote sensing image data set hosted on Amazon's AWS cloud service platform. It was jointly completed by Dig...

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Abstract

The invention relates to a remote sensing image target detection method based on deep learning, including: using remote sensing images to construct related data sets; The panchromatic sharpening model of the network; the object detection model based on the deep convolutional neural network is built, and the end-to-end training of the model is carried out by methods such as backpropagation and stochastic gradient descent; the end-to-end test of the built model is carried out. The invention has the advantage of high accuracy.

Description

technical field [0001] The invention relates to the fields of remote sensing image processing, deep learning, pattern recognition, etc., and in particular to a method based on deep learning and using a generative confrontation network to perform panchromatic sharpening processing and target detection on spectral images. Background technique [0002] Due to the limitation of signal transmission band and imaging sensor storage, most remote sensing satellites only provide multispectral (MSI) images with high spectral resolution, and panchromatic (PAN) images with high spatial resolution. Utilizing the complementary advantages of the two images, they are fused into a fused remote sensing image with clear spatial details and rich spectral information. This fusion technology is also known as panchromatic sharpening technology. [0003] At present, the mainstream panchromatic sharpening methods in the field of remote sensing include component replacement method and multi-scale anal...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/214G06F18/241
Inventor 侯春萍夏晗杨阳管岱莫晓蕾
Owner TIANJIN UNIV
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