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| Study on Feature Representation in Handwritten Numeral Recognition Based on Autoencoders |
| Shi Xueying |
| Sichuan University |
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Abstract This paper studies on several advanced Autoencoders like Sparse Autoencoder, Denoising Autoencoder, and Tiedweight
strategy for Autoencoder; explores on the principal of improving the feature representation with these Autoencoders, which
have been certificated in the handwritten numeral recognition. The performances of feature representation with these Autoencoders
are compared by setting the Autoencoders parameters. Experimental results show that the Sparse and Denoising strategies have great
improvment to the performance of Autoencoders.
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Published: 15 November 2017
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