Grain insect identification method and identification system based on feature fusion of SSD algorithm

A feature fusion and recognition method technology, applied in character and pattern recognition, calculation, computer parts and other directions, can solve the problem of inaccurate recognition of grain insects, and achieve the effect of being beneficial to recognition and positioning and solving poor accuracy

Active Publication Date: 2021-01-29
HENAN UNIVERSITY OF TECHNOLOGY
View PDF7 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a grain insect identification method and identification system based on feature fusion of SSD algorithm, to solve the problem of inaccurate identification of grain insects in the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Grain insect identification method and identification system based on feature fusion of SSD algorithm
  • Grain insect identification method and identification system based on feature fusion of SSD algorithm
  • Grain insect identification method and identification system based on feature fusion of SSD algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The purpose of the present invention is to provide a grain insect recognition method and recognition system based on the feature fusion of SSD algorithm, in which the depth feature layer and the shallow feature layer are fused in the established neural network model, and the K-means algorithm is used to obtain each The prior frame of the feature layer is used to solve the problem of inaccurate recognition of grain insects in the prior art.

[0046] Method example:

[0047] This embodiment provides a grain worm identification method based on feature fusion of SSD algorithm, and its process is as follows figure 1 shown, including the following steps:

[0048] Step 1: Create a dataset.

[0049] The training data in the dataset includes images of a variety of grain insects, including but not limited to corn weevil, red rice beetle, rice beetle, rusty flat rice beetle and Indian rice moth. When collecting images, live adults are used for shooting. Since live insects are m...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a grain insect identification method and identification system based on SSD algorithm feature fusion. The identification method comprises the following steps: establishing a data set; establishing a neural network model and training the neural network model by adopting the data set to obtain a trained neural network model; and collecting a to-be-identified grain insect image, inputting the to-be-identified grain insect image into the trained neural network model, and detecting the type and position of the grain insect in the to-be-identified grain insect image. According to the technical scheme provided by the invention, the output feature maps of the convolution layers conv43 and conv53 in the neural network model are fused, the block 11 unfavorable for small target detection is deleted, and the priori box suitable for the grain insect is obtained by adopting the Kmeans clustering algorithm, so that the defect of the default priori box in the original SSD is improved, the identification and positioning of the grain insect are facilitated, the problem that in the prior art, grain insect recognition accuracy is poor can be solved.

Description

technical field [0001] The invention relates to the technical field of grain insect identification, in particular to a grain insect identification method and identification system based on feature fusion of SSD algorithm. Background technique [0002] During the whole process of production, processing and storage, grain, oil and food will be attacked by stored grain pests. Grain worms will not only eat food and cause loss of food quantity, but also the products of their life metabolism will heat up food, aggravate the activity of food microorganisms, make food rotten and deteriorate, and may induce the production of microbial toxins. In addition, due to the existence of the dead bodies and excreta of pests in the food, the food is also polluted, the hygienic quality of the food is reduced, and the health of users is endangered. [0003] At present, with the development of computer technology, the informatization requirements of the grain industry are getting higher and high...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/23213G06F18/253G06F18/214
Inventor 吕宗旺金会芳孙福艳甄彤陈丽瑛邱帅欣桂崇文唐浩然
Owner HENAN UNIVERSITY OF TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products