Bird population recognition and analysis method based on GoogLeNet network model

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

Active Publication Date: 2018-02-23
SHANGHAI JIAO TONG UNIV
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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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  • Bird population recognition and analysis method based on GoogLeNet network model
  • Bird population recognition and analysis method based on GoogLeNet network model
  • Bird population recognition and analysis method 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 recognition and analysis method based on a GoogLeNet network model. A training picture sample database is established; a GoogLeNet network a capable of judging bird pictures is obtained by using picture samples to train the GoogLeNet network model; a GoogLeNet network b capable of accurately judging bird populations is obtained by using picture pictures totrain the GoogLeNet network model; frames of to-be-identified videos input in real time are decoded into to-be-identified picture flows; each frame of pictures in the picture flows is sequentially input into the GoogLeNet network a, and whether the pictures are bird pictures or not is judged; if yes, the pictures are input into the GoogLeNet network b, the included bird populations are identified; picture identification result flows are obtained, and final identification results are output from the picture identification result flows. The bird population recognition and analysis method fillsthe blank of bird population identification based on a deep learning model, the identification accuracy is high, and the identification results can be output and updated 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 Applications(China)
IPC IPC(8): G06F17/30G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06F16/51
Inventor 蒋兴浩孙锬锋许可
Owner SHANGHAI JIAO TONG UNIV
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