CVLGDec 30, 2020

LAIF: AI, Deep Learning for Germany Suetterlin Letter Recognition and Generation

arXiv:2101.10450v1Has Code
Originality Synthesis-oriented
AI Analysis

This research addresses the challenge of recognizing and generating historical German Sütterlin script, which is a niche problem for historians and archivists.

This paper proposes the Ludwig AI Framework (LAIF) for the recognition and generation of German Sütterlin letters. It utilizes a deep convolutional neural network for recognition and a deep generative adversarial network to synthesize handwritten letters, addressing the scarcity of training data.

One of the successful early implementation of deep learning AI technology was on letter recognition. With the recent breakthrough of artificial intelligence (AI) brings more solid technology for complex problems like handwritten letter recognition and even automatic generation of them. In this research, we proposed deep learning framework called Ludwig AI Framework(LAIF) for Germany Suetterlin letter recognition and generation. To recognize Suetterlin letter, we proposed deep convolutional neural network. Since lack of big amount of data to train for the deep models and huge cost to label existing hard copy of handwritten letters, we also introduce the methodology with deep generative adversarial network to generate handwritten letters as synthetic data. Main source code is in https://github.com/enkhtogtokh/LAIF repository.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes