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A medical company needs to take handwritten prescription and retrieve the text from it. To do this manually, it will require a lot of time and lots of cost to the company. So, the company wants to automate this task. You need to create a neural network model that will take images as input, read the text images, and convert it into digital text. To solve this problem, you need to create a CNN LSTM model. The aim of this project is to automatically convert handwritten text into machine encoded text.
The aim of this project is to automatically convert handwritten text into machine
The project has 4 major components:
1. Preprocess image and text data
2. Implementation of CNN layers to extract features
3. Implementation of RNN (Bi-LSTM) layers to the sequence model
4. CTC_loss and CTC_decode
This project can be used as final year project, capstone project, personal portfolio project, resume, proof of concept.