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Nondestructive identification for gender of chicken eggs based on GA-BPNN with double hidden layers
- Source :
- Journal of Applied Poultry Research, Vol 30, Iss 4, Pp 100203-(2021)
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- SUMMARY In order to identify the gender of chicken eggs at the early stage of incubation, a machine vision image acquisition system was constructed. Under the light source of LED, the images of 2 batches (186 and 180) of chicken eggs were respectively obtained on d 3, d 4, d 5, d 6, d 8, and d 10 of incubation. Considering the clarity and the integrity of blood vessels in the field of machine vision, the image of d 4 was determined as the basis for gender identification of chick embryos. After image processing, the 11 dimensions of feature parameters depicting the chick's embryonic development were extracted. In this paper, the genetic algorithm (GA) was used to optimize the initial weights and thresholds of backpropagation neural networks (BPNN) with different hidden layers. Then the GA-BPNN with single hidden layer, as well as, double hidden layers was established respectively. According to the research, the comprehensive accuracy of GA-BPNN model with double hidden layers reached 89.74% for the prediction set, which was higher than that of the model with single hidden layer, indicating that optimizing the initial weights and thresholds of BPNN by GA and adding the hidden layer had a certain effect on improving the recognition accuracy. Meanwhile, the results showed that the machine vision technology provided a feasible method for gender identification of chicken eggs at the early stage of incubation.
- Subjects :
- Artificial neural network
gender identification
business.industry
Machine vision
Pattern recognition
machine vision
BP neural network
TP368-456
Chick embryos
SF1-1100
Food processing and manufacture
Backpropagation
Animal culture
Identification (information)
Light source
Feature (computer vision)
genetic algorithm
Image acquisition
Animal Science and Zoology
Artificial intelligence
business
early stage of incubation
chicken eggs
Mathematics
Subjects
Details
- ISSN :
- 10566171
- Volume :
- 30
- Database :
- OpenAIRE
- Journal :
- Journal of Applied Poultry Research
- Accession number :
- edsair.doi.dedup.....093be57d1a5c6e553a9752f89661c17d
- Full Text :
- https://doi.org/10.1016/j.japr.2021.100203