Tide water identification and crisis early warning method based on YOLO technology

A tide and crisis technology, applied in the field of deep learning, can solve the problems of rare tide recognition and early warning

Pending Publication Date: 2020-07-14
ZHEJIANG SHUREN COLLEGE ZHEJIANG SHUREN UNIV
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AI Technical Summary

Problems solved by technology

[0005] Although the above-mentioned scholars focus on the use of YOLO technology to achieve various applications, there are few research reports on the application field of tide recognition and early warning. Because the tide has i

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  • Tide water identification and crisis early warning method based on YOLO technology
  • Tide water identification and crisis early warning method based on YOLO technology
  • Tide water identification and crisis early warning method based on YOLO technology

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Embodiment Construction

[0071] This embodiment discloses a method for tide identification and crisis early warning based on YOLO technology. The method is as follows: figure 1 As shown, the main steps are as follows:

[0072] (1) Use crawler technology to crawl tide images in Baidu pictures. Use the resize function of the opencv-python library to adjust the resolution of the image and add the corresponding label; use the getRotationMatrix2D function of the opencv-python library to rotate the image, the rotation angle is randomly generated, and the rotation range is 7 degrees to 15 degrees; Randomly move the pixel distance in the x-axis and y-axis directions, the movement range is 1-10 pixels, to realize the translation of the image; to make the image centrally symmetrical, to realize the symmetrical data enhancement of the image. After the data enhancement operations of translation, rotation, symmetry and scaling, a total of 1629 pictures of four different tide forms including horizontal tide, verti...

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Abstract

The invention discloses a tide water identification and crisis early warning method based on a YOLO technology, and the method comprises: building a tide water data set through the data enhancement operation of zooming, rotating, translation and symmetry, extracting the atmospheric refractive index through filtering, carrying out the color balance operation of an image, and selecting an atmospheric light component A; carrying out defogging by using a dark channel, carrying out defogging on the image, and carrying out white balance operation on the image, so that a clear image is obtained; andtraining the processed image by adopting a YOLO network to obtain a tide water identification model. According to the model, the input image is recognized, the position and height of tide water and the distance and time from the tide water to equipment are calculated, and early warning can be given out in time when danger occurs. The a tide water identification and crisis early warning method is abeneficial supplement to tide water identification and crisis early warning at present, can automatically monitor the state of tide water, makes up for the defects of manual patrol, reduces the personnel death rate caused by tidal bore, and avoids family tragedies.

Description

Technical field: [0001] The present invention relates to the field of deep learning technology, in particular to the field of regression-based target recognition methods, and specifically refers to a tide recognition and crisis early warning method based on YOLO technology. Background technique: [0002] The main reason for the tide injury incident is that people do not understand the characteristics of tide surges, they do not pay attention to them subjectively, and the competent department mainly uses regular patrolling and early warning to remind the masses. Due to limited manpower and coverage, the early warning effect is poor, so there is an urgent need for a tide identification And the crisis warning method, automatically identify the tide and give early warning of the crisis. [0003] In recent years, with the rapid development of deep learning technology, methods based on deep learning have been widely used in the field of object recognition. At present, the target ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06F16/951G06K9/36G06K9/46G06N3/04G06N3/08G06T5/00
CPCG06F16/951G06T5/003G06N3/084G06T2207/10024G06V20/13G06V10/20G06V10/56G06N3/045
Inventor 陈友荣熊振宇周亚娟陈鹏赵克华吕晓雯孙萍
Owner ZHEJIANG SHUREN COLLEGE ZHEJIANG SHUREN UNIV
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