Proposing Multimodal Integration Model Using LSTM and Autoencoder
We propose an architecture of neural network that can learn and integrate sequential multimodal information using Long Short Term Memory. Our model consists of encoder and decoder LSTMs and multimodal autoencoder. For integrating sequential multimodal information, firstly, the encoder LSTM encodes a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
European Alliance for Innovation (EAI)
2016-12-01
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| Series: | EAI Endorsed Transactions on Security and Safety |
| Subjects: | |
| Online Access: | http://eudl.eu/doi/10.4108/eai.3-12-2015.2262505 |