1. 基于权值分布的多模型分类算法研.
- Author
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蒋梦莹, 林小竹, 柯 岩, and 魏战红
- Subjects
- *
ARTIFICIAL neural networks , *FEATURE extraction , *DATA modeling , *CLASSIFICATION , *CURVES - Abstract
To improve the correct rate of image classification by convolutional neural network, this paper proposed a multimodel fusion convolutional neural network after research on the network structure. By extracting the output feature vectors of a single model and then fusing them, it obtained the new output feature vectors, and then set up a single classifier to classify the images, and improved the accuracy of the classification. By comparing the classification accuracy of single model and multimodel fusion, the class ification accuracy of multi-model fu sion convolutional neural network was improved. This paper analyzed the weight distribution of the last layer of the convolutional neural network, and found that the weight distribution curve of the same model on different data sets was similar and the weight distribution curve of the network model with better classification effect was more gentle. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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