Deep learning of invariant spatio-temporal features from video
We present a novel hierarchical and distributed model for learning invariant spatio-temporal features from video. Our approach builds on previous deep learning methods and uses the Convolutional Restricted Boltzmann machine (CRBM) as a building block. Our model, called the Space-Time Deep Belief Net...
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| Language: | English |
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University of British Columbia
2010
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| Online Access: | http://hdl.handle.net/2429/27651 |