Complex-valued neural networks (CVNNs) are a powerful modeling tool for domains where
data can be naturally interpreted in terms of complex numbers. However, several analytical …

Optical Character Recognition (OCR) is a technique that generates text from an image.
Recognizing the importance of OCR in real-world settings, a plethora of techniques have …

In Codice Ratio is a research project to study tools and techniques for analyzing the contents
of historical documents conserved in the Vatican Secret Archives (VSA). In this paper, we …

Convolutional Neural Networks (CNN) have achieved huge popularity in solving problems
in image analysis and in text recognition. In this work, we assess the effectiveness of CNN …

Handwritten recognition has received considerable attention in the domain of pattern
recognition, image processing, over the last few decades. As a consequence of this …

Abstract In Codice Ratio is a research project to study techniques for analyzing the contents
of historical documents conserved in the Vatican Apostolic Archives. In this paper, we …

Data rescuers worldwide have been trying to retrieve millions of valuable weather historical
records so the observations contained in those records are preserved, searchable …

To preserve handwritten historical documents, libraries are choosing to digitize them,
ensuring their longevity and accessibility. However, the true value of these digitized images …

Abstract Our project, In Codice Ratio, is an interdisciplinary research initiative for analyzing
content of historical documents conserved in the Vatican Secret Archives (VSA). As most of …

The design of activation functions is a growing research area in the field of neural networks.
In particular, instead of using fixed point-wise functions (eg, the rectified linear unit), several …