method: SROIE LSTM - Axel Alejandro Ramos García2020-05-28

Authors: Axel Alejandro Ramos García, Mario Daniel Chávez López

Affiliation: Instituto Tecnológico de Monterrey

Description: This is a method that tackles the key information extraction problem as a character-wise classification problem with a simple stacked bidirectional LSTM. The method first formats the text from an image into a single sequence. The sequence is then fed into a two-layer bidirectional LSTM to produce a classification label from 5 classes - 4 key information category and one "others" - for each character. The method consists in just a two-layer bidirectional LSTM implemented in PyTorch, and proves to sufficient in understanding the context of a receipt text and outputting highly accurate results.