Abstract
This paper uses deep learning related algorithms to classify and recognize the ethnic costume images of the Wa and Yi people. In the deep learning framework Tensorflow, the deep convolution network VGG model was migrated to the ethnic costume recognition task, and the image recognition of ethnic costume based on VGG was realized. By adjusting the size of the convolution kernel and the number of convolution layers of the VGGNet network model, a neural network model of ethnic costume image recognition suitable for the classification and recognition of the Wa and Yi people is constructed. By training the images in the ethnic costume image library, iteratively adjusting the parameters of Batch_size, Epoch, Dropout and other parameters of the network model, the comparative experiments are on, and the classification recognition rate of ethnic costume images under different network model parameters is analyzed.
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Acknowledgment
The research is supported by a National Nature Science Fund Project (61862068), Yunnan Key Laboratory of Smart Education, Program for innovative research team (in Science and Technology) in University of Yunnan Province, Kunming Key Laboratory of Education Information, and Starting Foundation for Doctoral Research of Yunnan Normal University (2017ZB013).
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Lei, Q., Wen, B., Ouyang, Z., Gan, J., Wei, K. (2020). Research on Image Recognition Method of Ethnic Costume Based on VGG. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12488. Springer, Cham. https://doi.org/10.1007/978-3-030-62463-7_29
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DOI: https://doi.org/10.1007/978-3-030-62463-7_29
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