The comparison of different graph convolutional neural networks for image recognition

Author:

Fu Sichao1,Yang Xinghao1,Liu Weifeng1

Affiliation:

1. China University of Petroleum (East China), Qingdao, China

Funder

Foundation of Shandong province

Fundamental Research Funds for the Central Universities, China University of Petroleum (East China)

National Natural Science Foundation of China

Publisher

ACM Press

Reference30 articles.

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2. B Yoshua, D Olivier and L.R Nicolas (2006). The curse of highly variable functions for local kernel machines. Advances in neural information processing systems, 107--114.

3. V Pascal, L Hugo, B Yoshua and M Pierre-Antoine (2008). Extracting and composing robust features with denoising autoencoders. Proceedings of the 25th international conference on Machine learning, 1096--1103.

4. M Tomas (2010). Recurrent neural network based language model. Eleventh Annual Conference of the International Speech Communication Association.

5. D Haluk and H Elliott (1987). Modeling and segmentation of noisy and textured images using Gibbs random fields. IEEE Transactions on pattern analysis and machine intelligence, 1987 (1), 39--55.

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