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Image main target detection method and device based on convolutional neural network

A convolutional neural network and target detection technology, which is applied in the field of image main target detection based on convolutional neural network, which can solve the problems that the model is only suitable for specific targets and images need to be manually labeled.

Pending Publication Date: 2019-08-30
PING AN TECH (SHENZHEN) CO LTD
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AI Technical Summary

Problems solved by technology

[0010] In view of this, the embodiment of the present invention provides a method and device for image main target detection based on convolutional neural network, which is used to solve the problem that the specific target of the image needs to be manually marked during model training in the prior art, and the trained model only needs to Questions for Specific Purposes

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  • Image main target detection method and device based on convolutional neural network
  • Image main target detection method and device based on convolutional neural network
  • Image main target detection method and device based on convolutional neural network

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Embodiment Construction

[0028] In order to better understand the technical solutions of the present invention, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0029] It should be clear that the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0030] Convolutional Neural Network (CNN for short) is a type of feedforward neural network (Feed forward Neural Networks) that includes convolution or related calculations and has a deep structure.

[0031] Convolutional neural network is a hierarchical model, mainly including input layer, convolutional layer, pooling layer, fully connected layer and output layer. Among them, the role of the input layer is to receive the input i...

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Abstract

The embodiment of the invention relates to the field of artificial intelligence, and provides an image main target detection method and device based on a convolutional neural network. The method comprises the steps of obtaining an input image; carrying out convolution layer processing on the input image to obtain a plurality of feature maps, and outputting the feature maps through a feature channel; according to the thermodynamic diagram of each feature channel, obtaining a saliency region on the feature diagram; carrying out clustering processing on the salient regions on the feature map to form a plurality of feature clusters; and determining the position of a main target on the input image based on the positions of all the feature clusters. According to the technical scheme, the problems that in the prior art, during model training, a specific target of an image needs to be manually labeled, and a trained model is only suitable for the specific target are solved.

Description

[0001] 【Technical field】 [0002] The present invention relates to the field of artificial intelligence, in particular to a convolutional neural network-based image main target detection method and device. [0003] 【Background technique】 [0004] With the development of deep learning technology, it has been widely used in visual recognition, image recognition and other fields. [0005] In the prior art, the specific target detection of an image adopts the following steps: [0006] Step 1. Obtain a large number of images containing a specific target, and mark the position information of the specific target on the image by manpower. For example, a bounding box is used to represent, and the four-dimensional vector P(x, y, w, h) of the bounding box is given to represent the position and size of the box, and then the model is obtained through training. [0007] Step 2. Use the trained model to extract specific objects in the newly acquired image. [0008] However, the existing te...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V10/462G06V2201/07G06N3/045G06F18/23G06F18/24
Inventor 李锴
Owner PING AN TECH (SHENZHEN) CO LTD
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