Due to the advancement of technology and computing, digitization of printed or handwritten
text has become popular these days. Artificial Intelligence (AI), plays an important role in the …

Annotating words in a historical document image archive for word image recognition
purpose demands time and skilled human resource (like historians, paleographers). In a …

Historical records are invaluable sources of information that provide insights into multiple
aspects of past events and societies. The analysis of historical records using deep learning …

Zero-Shot Learning (ZSL) techniques could classify a completely unseen class, which it has
never seen before during training. Thus, making it more apt for any real-life classification …

Handwriting recognition has seen significant success with the use of deep learning.
However, a persistent shortcoming of neural networks is that they are not well-equipped to …

Annotating words in a historical document image archive for word image recognition
purpose demands time and skilled human resource (like historians, paleographers). In a …

In this thesis, we make a bridge from the past to the future by using artificial-intelligence
methods for text recognition in a historical Dutch collection of the Natuurkundige Commissie …

In text recognition, complex glyphs and tail classes have always been factors affecting
model performance. Specifically for Chinese text recognition, the lack of shape-awareness …

In recent years, long short-term memory neural networks (LSTMs) followed by a
connectionist temporal classification (CTC) have shown strength in solving handwritten text …

In real-world applications, new data, patterns, and categories that were not covered by the
training data can frequently emerge, necessitating the capability to detect and adapt to novel …