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Found 3 papers, 3 papers with code
Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes
The CTC confidences are computed on the encoder while the Transformer is only used for character-wise S2S decoding.
Optimizing small BERTs trained for German NER
Currently, the most widespread neural network architecture for training language models is the so called BERT which led to improvements in various Natural Language Processing (NLP) tasks.
Evaluating Sequence-to-Sequence Models for Handwritten Text Recognition
Encoder-decoder models have become an effective approach for sequence learning tasks like machine translation, image captioning and speech recognition, but have yet to show competitive results for handwritten text recognition.
Ranked #9 on
Handwritten Text Recognition
on IAM
