GAN-based electric power place pest motion blurred image detection method
A technology for motion blurred images and harmful organisms, applied in biological neural network models, image enhancement, image data processing, etc., can solve problems such as equipment damage in power places, video defocus, and inability to effectively identify harmful organisms, etc., to achieve The effect of avoiding loss and reducing loss
Inactive Publication Date: 2019-11-19
FUZHOU UNIV
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[0002] Existing machine learning-based harmful organism detection systems in power places generally use the traditional manual feature extraction method of "complex image preprocessing-artificial design features-calculation of artificial features-machine learning". In the on-duty electric power place, because the harmful organisms (such as mice, snakes, etc.) appearing in it have the characteristics of fast action, in the surveillance video, the images often have problems of motion blur and video defocusing. Using traditional The image detection method cannot effectively identify the invasion of harmful organisms, which will cause damage to the equipment in the power site
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[0047] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0048] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0049] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...
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The invention relates to a GAN-based electric power place harmful organism motion blurred image detection method, which comprises the steps of introducing a generative adversarial network M1, restoring a motion blurred image in an input image into a clear image, and performing training by utilizing labeled harmful animal samples to obtain a trained neural network model M2; and enabling the input picture to pass through M1 and M2 in sequence to obtain a detection result. According to the invention, harmful organism invasion information can be detected more accurately.
Description
technical field [0001] The invention relates to the technical field of detection of harmful organisms in electric power places, in particular to a method for detecting motion blurred images of harmful organisms in electric power places based on GAN. Background technique [0002] Existing machine learning-based harmful organism detection systems in power places generally use the traditional manual feature extraction method of "complex image preprocessing-artificial design features-calculation of artificial features-machine learning". In the on-duty electric power place, because the harmful organisms (such as mice, snakes, etc.) appearing in it have the characteristics of fast action, in the surveillance video, the images often have problems of motion blur and video defocusing. Using traditional The image detection method cannot effectively identify the invasion of harmful organisms, which will cause damage to the equipment in the power place. Contents of the invention [0...
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IPC IPC(8): G06K9/62G06N3/02G06T5/00
CPCG06N3/02G06F18/24G06F18/214G06T5/00
Inventor 钟尚平叶东阳陈开志
Owner FUZHOU UNIV