Parametric Learning of Texture Filters by Stacked Fisher Autoencoders
Deep learning has recently contributed significantly to large-scale recognition of several modalities like image, video and speech. Stacked autoencoders are a family of powerful convolutional neural nets to build scalable generative models for automatic feature learning. In this paper, we propose a...
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| Published in: | 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA) pp. 1 - 8 |
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| Main Author: | |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
01.11.2016
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| Subjects: | |
| Online Access: | Get full text |
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