Abstract
In order to improve the effect of vegetable image recognition, a neural network algorithm was proposed. Firstly, radial basis function neural network model was established, including gradient descent method for solving the weight parameters. K-means clustering method increasing the radius of neighborhood was calculated implicit function center value, and the nuclear width was used adjacent cluster centers. Secondly, quantum genetic algorithm was deleted the redundant weights and neuron. Thirdly, vegetable image feature extraction was extracted. Finally, the process was given. The simulation results showed that the average recognition rate of shape feature was 97.56%, and the texture feature was 95.60%. Moreover, the color feature was found 93.25%, after trained for 5.83 s, and the average recognition time was 2.18 s. The algorithms we reported here was found better than other kinds.
Publication Date
2-28-2020
First Page
146
Last Page
150
DOI
10.13652/j.issn.1003-5788.2020.02.027
Recommended Citation
Fan, LU
(2020)
"Vegetable image recognition based on improved neural network algorithm,"
Food and Machinery: Vol. 36:
Iss.
2, Article 27.
DOI: 10.13652/j.issn.1003-5788.2020.02.027
Available at:
https://www.ifoodmm.cn/journal/vol36/iss2/27
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