Deep Relational Model: A Joint Probabilistic Model with a Hierarchical Structure for Bidirectional Estimation of Image and Labels
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Summary
In the image recognition experiments, it is observed that the DRM outperformed DNNs even without fine-tuning, and in the image generation experiments, the DRM obtained much more realistic images generated more than those from the other generative models.
- Type
- article
- Published
- 2018-01-01
- Cited by
- 3
- References
- 23
- Access
- Open access
- OpenAlex
- https://openalex.org/W2790969636
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:7561920
Keywords
MNIST database, Computer science, Deep belief network, Boltzmann machine, Artificial intelligence
References
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- Deep Learning: Methods and Applications
- 3D Object Recognition with Deep Belief Nets
- Learning Deep Energy Models
- Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines
- Voice conversion in high-order eigen space using deep belief nets
- Modeling deep bidirectional relationships for image classification and generation
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