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

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 ...

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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 its specific moving form and movement speed, the above-mentioned current situation of YOLO technology None of the methods are directly applicable to the identification and early warning of tides. In view of this, this case was born

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