Target detection algorithm based on twin neural network

A target detection algorithm and neural network technology, applied in biological neural network models, neural learning methods, neural architectures, etc., can solve problems such as insufficient recognition accuracy and insufficient information utilization, and achieve high detection accuracy and fast running speed.

Inactive Publication Date: 2019-12-03
JIANGSU ELECTRIC POWER CO +1
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AI Technical Summary

Problems solved by technology

[0006] In the actual application scene of continuous shooting, the current target detection algorithm is insufficient for the information of the captured image, and the recognition accuracy is not enough. The purpose of the present invention is to provide a target detection algori

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  • Target detection algorithm based on twin neural network
  • Target detection algorithm based on twin neural network
  • Target detection algorithm based on twin neural network

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[0033] The algorithm of the present invention will be further described below in conjunction with the drawings and specific implementations.

[0034] The present invention is a target detection algorithm based on a twin neural network. The following will take the detection of birds on a transmission line as an example to illustrate the use process of the algorithm. The implementation steps of the algorithm include: preparing a data set that matches the actual application scenario; training the algorithm; and using the algorithm.

[0035] figure 1 It is the network structure diagram of the present invention. figure 1 Among them, image 1 is a picture that does not contain the detected object, and is used as a reference to compare with the picture to be detected. Image 2. This image is the image to be detected. 3 (Network1) is the image feature extraction network, which will perform feature extraction on the image. 4 (Network2) is the feature extraction network of the image, with th...

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Abstract

The invention discloses a target detection algorithm based on a twin neural network. The target detection algorithm comprises the following steps: collecting images continuously shot at a fixed visualangle; calculating the similarity between the to-be-detected image and the reference image by using a twin neural network; and quickly finding out changed targets in the scene by utilizing a similarity analysis result between the to-be-detected image and the reference image, and classifying the targets. Aiming at the characteristics of the continuously acquired images, the information relevance among the plurality of images is considered, the information among the plurality of continuous images is fully explored, and the detection speed is improved while the detection precision is improved. The method is suitable for target detection of images which are continuously shot at a fixed angle.

Description

technical field [0001] The invention relates to an image target detection method, in particular to a twin neural network-based target detection algorithm suitable for fixed-angle, continuously captured images. Background technique [0002] Target detection refers to identifying a target object in an image, and then marking the position of the object in the image. Currently, a rectangular frame is used to mark the target object. [0003] The accuracy and speed of traditional target detection algorithms in the current application cannot keep up with the target detection algorithms based on deep learning. Therefore, the current mainstream target detection algorithms are basically based on deep learning. Most of the algorithms are A convolutional neural network is used. These algorithms use convolutional neural networks to extract the features of objects in the image, but in this process, there is a big disadvantage that after performing multiple convolution and pooling and oth...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06V20/20G06V2201/07G06N3/045
Inventor 陈咏秋孙凌卿张永泽
Owner JIANGSU ELECTRIC POWER CO
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