
Simple architectural and training modifications, such as retaining aspect ratio, using max-pooling, and adding a CTC shortcut, can significantly improve the performance of basic convolutional-recurrent handwritten text recognition systems.


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simple-yet-effective-modifications-for-improving-handwritten-text-recognition-systems


Simple Yet Effective Modifications for Improving Handwritten Text Recognition Systems


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Incorporating explicit n-gram language models significantly improves the performance of state-of-the-art deep learning architectures for handwritten text recognition, challenging the notion that deep learning models alone are sufficient for optimal performance.


enhancing-handwritten-text-recognition-with-explicit-n-gram-language-models


Enhancing Handwritten Text Recognition with Explicit N-Gram Language Models
