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Table 1 Neural network parameters for networks used to test character embeddings and padded vs. non-padded convolutonal layers

From: Improving deep neural network design with new text data representations

1-ofm vs. log(m) embedding
  log-m 1-of-m
Convolutional layer Number of filters Filter Pool Number of filters Filter Pool
1 32 \(3 \times 3\) 32 \(3 \times 3\) \(2 \times 2\)
2 32 \(3 \times 3\) 32 \(3 \times 3\) \(2 \times 2\)
3 32 \(3 \times 3\) \(2 \times 2\) 32 \(3 \times 3\) \(2 \times 2\)
Dense layer Number of neurons Number of neurons
1 512 1024
2 512 1024
3 2 2
Padded vs. non-padded
  Deep padded Padded/non-padded
Convolutional layer Number of filters Filter Pool Number of filters Filter Pool
1 128 \(3 \times 3\) 128 \(3 \times 3\)
2 128 \(3 \times 3\) 128 \(3 \times 3\)
3 128 \(3 \times 3\) \(2 \times 2\) 128 \(3 \times 3\) \(2 \times 2\)
4 128 \(3 \times 3\)
5 128 \(3 \times 3\)
6 128 \(3 \times 3\) \(2 \times 2\)
Dense layer Number of neurons Number of neurons
1 512 1024
2 512 1024
3 2 2