Layered Feature Recognition Algorithm Based on Combined Convolution
Shuduo Zhao,
Xu Han,
Jin Xu,
Haiyun Chen,
Guanqin Feng,
Chenxin Ma,
Wenhao Zhou
Issue:
Volume 7, Issue 4, August 2019
Pages:
99-110
Received:
19 November 2019
Accepted:
11 December 2019
Published:
24 December 2019
Abstract: In recent years, the deep learning algorithms were gradually understood and accepted. It needs to take too many samples to train. Since the implementation of deep learning algorithm, it seems that the past classical algorithms have become gloomy. In this paper, we get an intelligent pattern recognition model by combining some classical algorithms in the past and extrapolating the convolution algorithm. This new model is based on a single regular sample, with its advanced generalization capabilities far beyond those of deep learning algorithms. Experimental results on MNIST, QMNIST, CMU PIE and Extended Yale B databases indicate that the proposed model is better than the related methods as compared with.
Abstract: In recent years, the deep learning algorithms were gradually understood and accepted. It needs to take too many samples to train. Since the implementation of deep learning algorithm, it seems that the past classical algorithms have become gloomy. In this paper, we get an intelligent pattern recognition model by combining some classical algorithms i...
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