Application of Advanced BP Neural Network in Image Recognition
| Autor: | Jin Hongjiao |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Artificial neural network
Computer science Generalization business.industry Computer Science::Neural and Evolutionary Computation Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) 02 engineering and technology Image (mathematics) Rate of convergence Computer Science::Computer Vision and Pattern Recognition Genetic algorithm Convergence (routing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business |
| Zdroj: | 2019 18th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES). |
| DOI: | 10.1109/dcabes48411.2019.00012 |
| Popis: | In order to improve the accuracy and speed of image recognition, an improved image recognition algorithm is designed based on genetic algorithm and BP neural network as results of the traditional BP neural network has problems such as structural parameter uncertainty, low convergence rate and local minimum value. Firstly, the color and texture feature of the image are extracted. BP neural network structure parameters are optimized by using BP neural network based on the genetic algorithm. The image recognition process is presented and the image recognition result is integrated according to the evidence theory to obtain the complete image information. The simulation results show that the algorithm has high recognition rate and convergence speed. Under the condition of a small number of training samples, BP neural network still has better generalization ability. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|