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Pytesseract OCR model to identify texts. Incorporated a pre-trained Named Entity Recognition (NER) model to extract entities from the identified texts, interpreted the information by text mining and web searches to collect auxiliary information.
Experiment with three different models: conditional random field (CRF), bidirectional long short-term memory (BiLSTM), and a combination of the two, and their performances on two named entity recognition (NER) datasets.