About this document
Handwriting Generation with RNNs by Abdul Wase is a document available to read on EtoBox.
The document discusses using recurrent neural networks (RNNs) to generate realistic handwriting. Specifically, it proposes using long short-term memory (LSTM) RNNs, which are better able to store and access information over long periods of time compared to standard RNNs. The system would take in handwriting samples, train an LSTM model on the data, and then be able to generate new text in a style similar to the input samples. This could have applications in forensics and psychology to analyze individuals
- Author
- Abdul Wase
- Language
- EN