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Method and platform for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and deep neural network

A deep neural network and remote sensing data technology, applied in the field of dynamic monitoring of typical features in mining, can solve the problems of insufficient accuracy and real-time performance of typical features, low spatial resolution of remote sensing images, complex mining environment, etc. Translation time, good relevance, and the effect of improving build speed

Pending Publication Date: 2020-10-02
ANHUI ZHONGKE INTELLIGENT PERCEPTION BIG DATA IND TECH RES INST CO LTD
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Problems solved by technology

[0004] The purpose of the present invention is to provide a dynamic monitoring method and platform for typical ground features in mining based on multi-source remote sensing data fusion and deep neural network to solve the problem of poor recognition effect due to the low spa

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  • Method and platform for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and deep neural network
  • Method and platform for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and deep neural network
  • Method and platform for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and deep neural network

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[0040] The specific embodiments of the present invention will be further described in detail by describing the embodiments below with reference to the accompanying drawings, so as to help those skilled in the art have a more complete, accurate and in-depth understanding of the inventive concepts and technical solutions of the present invention.

[0041] Such as Figure 1-3 As shown, the present invention provides a method and platform for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and deep neural network, including the following steps:

[0042] The invention provides a method for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and deep neural network. The method includes the following steps:

[0043] Step 1: Acquisition of time-series multi-source remote sensing data and ground survey of mine basic data; specifically include the following steps:

[0044] Step...

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Abstract

The invention discloses a method and platform for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and a deep neural network. The method includes: 1) acquiring time-series multi-source remote sensing data and basic mine data; 2) processing the remote sensing data and performing fusion of multi-source heterogeneous data to obtain enhanced remote sensing images of high-resolution multi-spectral images; 3) constructing a deep neural network model, and performing intelligent extraction on typical ground features by a method combining the deepneural network and artificial visual interpretation; 4) performing online dynamic monitoring and data analysis management on the extracted typical features. This method can improve the spatial resolution of remote sensing data images and it is easier to identify typical features after enhancing the image. At the same time, the machine interpretation manner adopted can efficiently and accurately identify the typical features, so that the typical features of mines can be online monitored in real time.

Description

technical field [0001] The invention relates to a method and platform for dynamic monitoring of typical ground objects in mining based on multi-source remote sensing data fusion and deep neural network. Background technique [0002] Due to the lack of organization and information mining of multi-source spatio-temporal remote sensing data, traditional mine monitoring is only a qualitative or semi-quantitative description of the ore body position and area indicators of framed images, and does not truly monitor spatio-temporal dynamic changes. If multi-source spatio-temporal remote sensing data is introduced, the high temporal resolution makes the update frequency of remote sensing data faster, and high time-frequency dynamic monitoring of mines can be carried out; the high spectral resolution makes the identification of mines and ground features more accurate, but the spatial resolution The clarity of images collected on the ground is often not achieved. In addition, the envir...

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/254G06F18/253
Inventor 张炜
Owner ANHUI ZHONGKE INTELLIGENT PERCEPTION BIG DATA IND TECH RES INST CO LTD
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