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About 3-D Object Recognition With Deep Belief Nets
The document describes a new type of top-level model for deep belief nets that uses a third-order restricted Boltzmann machine. It evaluates the model on an object recognition task using the NORB dataset and achieves an error rate close to the best published convolutional neural network result. The model significantly outperforms SVMs and achieves a lower error rate than convolutional neural networks when given additional unlabeled data.
Detailed Information
| Author: | ['alan1966'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 9 |
| Language: | English |
| Format: | |
| Price: | FREE |
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