Sagar-modelling/Handwriting_Recognition_CRNN_LSTM
In this notebook, we'll go through the steps to train a CRNN (CNN+RNN) model for handwriting recognition. The model will be trained using the CTC(Connectionist Temporal Classification) loss.
This project helps convert handwritten text from images into machine-readable digital text. You provide images containing handwritten lines, and it outputs the transcribed text. It's designed for data scientists and AI/ML engineers working on automated document processing.
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Use this if you need to build or customize a deep learning model for Optical Character Recognition (OCR), specifically for handling handwritten content.
Not ideal if you're looking for an off-the-shelf OCR application without needing to train or understand the underlying deep learning architecture.
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Oct 17, 2021
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