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Identification and analysis method of bird population based on googlenet network model

A network model and analysis method technology, applied in the field of bird identification, can solve the problems of no explanation or report found, no data collected, etc., to achieve the effect of improving credibility, real-time output, and high recognition accuracy.

Active Publication Date: 2021-08-17
SHANGHAI JIAOTONG UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0008] At present, there is no description or report of similar technology to the present invention, and no similar information has been collected at home and abroad

Method used

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  • Identification and analysis method of bird population based on googlenet network model
  • Identification and analysis method of bird population based on googlenet network model
  • Identification and analysis method of bird population based on googlenet network model

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Embodiment

[0051] Such as figure 1 As shown, the present embodiment provides a method for intelligent identification and analysis of bird populations based on the GoogLeNet network model, and its steps mainly include:

[0052] Step 1, use MySQL to make a sample management tool, establish a training image sample database, and obtain a sample database for training the GoogLeNet network model;

[0053] Step 2, train the GoogLeNet deep learning network model with different types of picture samples, and obtain the GoogLeNet network 1 that can distinguish whether it is a bird picture;

[0054]Step 3, train the GoogLeNet deep learning network model with pictures of different types of birds, and obtain the GoogLeNet network 2 that can accurately distinguish the species of birds;

[0055] Step 4, deframing the real-time input video to be recognized into a picture stream to be recognized;

[0056] Step 5, for each frame of pictures in the picture stream obtained in step 4, input the GoogLeNet ne...

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Abstract

The invention discloses a bird population identification and analysis method based on a GoogLeNet network model. Establish a training image sample database; use image samples to train the GoogLeNet network model, and obtain a GoogLeNet network a that can judge whether it is a bird picture; use bird pictures to train the GoogLeNet network model, and obtain a GoogLeNet network b that can accurately identify bird populations; for real-time The input video to be identified is deframed into a picture stream to be identified; each frame of the picture in the picture stream is input into GoogLeNet network a in turn to determine whether it is a bird picture; if it is, input the picture into GoogLeNet network b to identify the birds contained in it Population; get the image recognition result flow, and output the final recognition result from the recognition result flow. The invention fills in the blank of using the deep learning model to identify bird populations, has high identification accuracy, and can output and update the identification results in real time.

Description

technical field [0001] The invention relates to a method for identifying birds, in particular to an intelligent identification and analysis method for bird populations based on a GoogLeNet network model. Background technique [0002] As the development of industrial society brings more and more heavy burdens to nature, people pay more and more attention to the harmonious coexistence between man and nature. Compared with the traditional zoo watching, more and more tourists prefer the semi-open animal sightseeing area similar to Niaoyulin. Taking the bird zoo as an example, this kind of open zoo often sets up a large net frame above the valley to form a relatively closed large space, where different types of birds fly and inhabit freely, and visitors can watch more lively Birds, fully enjoy the beauty and fun of nature. [0003] However, in such zoos, due to the greater mobility of birds and the difficulty in determining their habitats, how to set up signs to introduce infor...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/51G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06F16/51
Inventor 蒋兴浩孙锬锋许可
Owner SHANGHAI JIAOTONG UNIV