Intelligent cattle farm monitoring and recognition method and device based on deep learning

A technology of deep learning and identification methods, applied in the field of monitoring and identification methods and devices of smart cattle farms, to achieve the effects of increasing sparsity, small amount of calculation, and good generalization performance

Inactive Publication Date: 2020-12-18
四川圣点世纪科技有限公司
View PDF7 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the application of the faster rcnn network to the target detection of animal groups has not been reported

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
  • Intelligent cattle farm monitoring and recognition method and device based on deep learning
  • Intelligent cattle farm monitoring and recognition method and device based on deep learning
  • Intelligent cattle farm monitoring and recognition method and device based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] refer to figure 1 , the present embodiment provides a method for monitoring and identifying smart cattle farms based on deep learning, including the following steps:

[0058] 1) Dataset production. The monitoring equipment is installed on the top of the cowshed, and the shooting pictures can be displayed on the monitoring equipment. Capture pictures of cattle from monitoring equipment, such as figure 2 .

[0059] 2) Use labeling software for labeling. A total of 100 cows will be labeled. In order to make a better data set, each cow with a relatively complete body must be selected for labeling, and 1000 pictures will be labeled as a data set. , of which 900 are the training set and 100 are the test set.

[0060] 3) Use the training set obtained in 2) to perform classification regression and position regression through the target detection network Faster rcnn to obtain the position of the cow on the picture and its confidence level. The confidence threshold is set to...

Embodiment 2

[0079] refer to Figure 7 , a monitoring and identification device for a smart cattle farm based on deep learning, which includes:

[0080] 1) The collection module collects pictures of cattle in the cattle farm through video monitoring equipment; the collection module is used to realize the function of step 1) of embodiment 1.

[0081] 2) The labeling module is used to label the cattle in the pictures of the cows in the cattle farm to make a training set; the labeling module is used to realize the function of step 2) of the embodiment 1.

[0082] 3) The first training module, input the training set obtained by the labeling module into the target detection network faster rcnn, and train to obtain the herd target detection model; the first training module is used to realize the function of step 3) of embodiment 1.

[0083] 4) The detection module uses the cattle target detection model to detect the cattle video to be recognized, and selects the position of each frame of the ca...

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 an intelligent cattle farm monitoring and recognition method and device based on deep learning, and the method comprises the following steps: 1) collecting cattle flock pictures of a cattle farm through video monitoring equipment; 2) marking the cattle in the cattle farm cattle flock picture to form a training set; 3) inputting the training set in the step 2) into a targetdetection network master rcnn, and training to obtain a cattle group target detection model; 4) selecting the position of each frame of cattle in the video; 5) numbering different cows to form a training set; 6) training to obtain a cattle identification model; and 7) carrying out identity identification, and visualizing an identification result to the back of the cattle. According to the invention, the number of cattle groups in a cattle farm can be accurately counted in real time; and identity training is carried out on the box-selected cattle back by using a residual network to successfully confirm the identity of the numbered cattle. Therefore, the monitoring and identification method provided by the invention can perform complete monitoring and identity identification on the cattle flock in the cattle farm.

Description

technical field [0001] The invention relates to the field of target detection and target recognition, in particular to a monitoring and recognition method and device for a smart cattle farm based on deep learning. Background technique [0002] As the leading industry of the agricultural and rural economy, animal husbandry has become a basic industry to ensure the consumption of meat, eggs, milk and animal protein intake of urban and rural residents. Provincial and regional poverty alleviation measures. Dairy and beef cattle breeding is an important part of the entire agriculture and occupies an important position in the agricultural economic system. In the current breeding industry, the emergence of strong infectious diseases such as mad cow disease and foot-and-mouth disease has a great impact on the quality and safety of dairy products and livestock products. Therefore, fine breeding of individuals is the main research direction of modern farming. [0003] As the animal ...

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): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/40G06V20/52G06N3/045G06F18/214
Inventor 赵国栋张烜李学双
Owner 四川圣点世纪科技有限公司
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