- The model uses ResNet50 as the image feature extractor, the feature maps are downsampled by a factor of 4 with respect to the input image, which is then followed by stacked BiLateral LSTM layers to learn the sequence of characters.
- Finally a softmax classifier outputs a probablity distribution, which the CTC loss uses to decode the final sequence
- The model was trained on 100,000 synthetically generated word images, with the number of words varying between 1 and 4
