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Recognition Method of Odonata Insects Based on Region Proposal Network

A recognition method and insect technology, applied in the field of recognition, can solve problems such as difficult recognition and complex background of pictures of Odonata insects, and achieve the effect of solving difficult recognition and enhancing the ability to extract effective features

Active Publication Date: 2022-06-03
CHONGQING NORMAL UNIVERSITY
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  • Summary
  • Abstract
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Problems solved by technology

[0004] In view of this, the purpose of the present invention is to overcome the defects in the prior art and provide a method for identifying Odonata insects based on the region suggestion network, which can make the identification process simple and fast, save a lot of labor costs, and solve the problem of Odonata insects in the natural environment. The complex background of insect pictures makes recognition difficult

Method used

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  • Recognition Method of Odonata Insects Based on Region Proposal Network
  • Recognition Method of Odonata Insects Based on Region Proposal Network
  • Recognition Method of Odonata Insects Based on Region Proposal Network

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Embodiment Construction

[0043] In the present embodiment, the Odonata insect image is the Odonata insect image under the natural environment. Among them, the collected

[0047] S42. Use ResNet50 as the feature extraction network of the deep convolutional network model, and use the region proposal network as the

[0048] S43. Determine the loss function of the deep convolutional network model. Among them, by introducing the loss function, and adding the super

[0050] L=L

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Abstract

The invention discloses a method for identifying Odonata insects based on a region suggestion network, comprising the steps of: S1. Cleaning and arranging images of Odonata insects to obtain a data set of Odonata insect images; S2. Data of Odonata insect images The data set is enhanced to obtain an enhanced data set; S3. divide the enhanced data set to obtain a training set, a verification set and a test set of images of Odonata insects; S4. Construct a deep convolution based on the region proposal network Product network model; S5. use the training set and verification set to train the deep convolution network model to obtain the trained network model; S6. input the test set to the trained network model, and output the test to obtain the The classification results of the set. The invention can make the recognition process simple and fast, save a lot of labor costs, and solve the problem of difficult recognition caused by complicated backgrounds of pictures of Odonata insects in the natural environment.

Description

Identification of Odonata Insects Based on Region Proposal Network technical field The present invention relates to identification field, be specifically related to a kind of Odonata insect identification method based on regional suggestion network. Background technique The existing Odonata automatic identification algorithm takes the feature of human hand-designed as the classification basis, and uses the traditional recognition algorithm. The recognition framework is constructed in other ways, only the specimen pictures of several species of dragonflies can be recognized, and the recognition rate is low, which is not suitable for the natural environment. Dragonfly pictures with complex backgrounds do not have the ability to identify; [0003] Existing insect automatic identification algorithms are often divided into two steps to achieve. The first step is detection. that is to be known first The implementation of the detection algorithm for different targets, this ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/10G06V10/40G06V10/774G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/00G06V10/40G06N3/045G06F18/24G06F18/214
Inventor 皮家甜于昕彭明杰吴志友
Owner CHONGQING NORMAL UNIVERSITY
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