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Deep Learning for Handwritten Text Recognition by made.sadhu is a document available to read on EtoBox.

What is Deep Learning for Handwritten Text Recognition about?

This research paper presents a novel approach to Handwritten Text Recognition (HTR) using a hybrid Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model, achieving a Character Error Rate (CER) of 4.57% and Word Error Rate (WER) of 12.3% on the IAM dataset. The model effectively captures spatial and sequential dependencies in handwritten text, demonstrating superior performance compared to traditional Optical Character Recognition (OCR) methods. The findings highlight the potential appli

Author

made.sadhu

Language

EN