Picture blind source separation by auto-encoder identity mapping with structural pruning
説明
A non-information-theoretic approach applied here for BSS of image data (pictures) is based on an auto-encoder neural network that incorporates a pruning algorithm. Nonlinear hidden units that survive the pruning will be the source extractors. The BSS state is attained as a local minimum of the error associated with the identity mapping by the auto-encoder. An internal mixing model is automatically induced in the decoder part. The BSS performance is shown to be satisfactory, including trouble cases involving noise or blanks in the mixed pictures.
収録刊行物
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- Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02.
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Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02. 1393-1397, 2004-04-23
Nanyang Technol. Univ