Name
Abstract | ||
|---|---|---|
This article presents our proposed system combining a Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) for the visual question answering applied in the medical images characterization.
In our proposed Encoder-Decoder Model we have used a pre-trained convolutional neural network to extract image features, a pre-trained word embedding for questions-answers representation.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3368756.3369093 | Proceedings of the 4th International Conference on Smart City Applications |
Keywords | DocType | ISBN |
CNN, LSTM, NLP, RNN, computer vision, encoder-decoder, greedy search, transfer learning, visual question answering, word embedding | Conference | 978-1-4503-6289-4 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bghiel Afrae | 1 | 0 | 0.34 |
| Dahdouh Yousra | 2 | 0 | 0.34 |
| Imane Allaouzi | 3 | 0 | 1.35 |
| Mohamed Ben Ahmed | 4 | 195 | 45.34 |
| Anouar A. Boudhir | 5 | 4 | 3.87 |