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Machine-vision-based land use planning method and system, and electronic device

A machine vision and recognition system technology, applied in the direction of instruments, computer components, biological neural network models, etc.

Active Publication Date: 2018-04-17
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the planning of agricultural reclamation and forest land use based on machine learning object recognition and segmentation technology is still blank

Method used

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  • Machine-vision-based land use planning method and system, and electronic device
  • Machine-vision-based land use planning method and system, and electronic device
  • Machine-vision-based land use planning method and system, and electronic device

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Embodiment Construction

[0097] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

[0098] see figure 1 , is a flow chart of the machine vision-based land use planning method according to the first embodiment of the present application. The land use planning method based on machine vision according to the first embodiment of the present application includes the following steps:

[0099] Step a: collecting terrain image data of the target area;

[0100] Step b: Construct a convolutional neural network model based on "area convolutional neural network branch + object area full convolution branch";

[0101] Step c: Input the collected topographic image data into the convo...

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Abstract

The application relates to the field of landform segmentation and identification technologies, in particular, to a machine-vision-based land use planning method and system, and an electronic device. The method comprises: collecting landform image data of a target area; constructing a convolutional neural network model based on a regional convolution neural network branch and an object area full-convolution branch; inputting the collected landform image data into the convolutional neural network model based on a regional convolution neural network branch and an object area full-convolution branch, extracting landform features of all landform objects in the landform image data by the convolutional neural network model, carrying out landform object classification and landform region segmentation based on the landform features; and determining landform composition of the target area based on the landform object classification and landform region segmentation results and carrying out land use planning on the target area. Therefore, lots of manual outdoor surveying and mapping work is reduced; the restrictions of application scenes are reduced; the application range is extended; and therecognition accuracy is improved.

Description

technical field [0001] The present application relates to the technical field of terrain segmentation and recognition, in particular to a machine vision-based land use planning method, system and electronic equipment. Background technique [0002] Image processing and computer vision refer to the use of cameras and computers instead of human eyes to identify, track and measure machine vision, and further use computers for image processing to generate images that are more suitable for human eyes to observe or sent to instruments for detection. [0003] The application of machine learning has the advantages of high accuracy and fast recognition speed in image (video) recognition. Machine learning is a branch of artificial intelligence. The research of artificial intelligence is a natural and clear thread from focusing on "reasoning" to focusing on "knowledge" and then focusing on "learning". Obviously, machine learning is a way to realize artificial intelligence, that is, us...

Claims

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Application Information

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IPC IPC(8): G06K9/34G06K9/46G06N3/04
CPCG06V10/267G06V10/40G06N3/045
Inventor 王书强曹松王祖辉胡明辉王鸿飞
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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