Siberian Federal University: Russian Scientists Have Taught a neural network to read handwritten Letters of the Russian Alphabet

Siberian Federal University: Russian Scientists Have Taught a neural network to read handwritten Letters of the Russian Alphabet . “SibFU scientists have developed a new convolutional neural network (CNN) capable of recognizing images of handwritten letters with high accuracy. The resulting algorithm transforms the image and recognizes the letter encrypted in it. According to the scientists, the algorithm’s accuracy is 99 %.”

University of Connecticut: UConn Library, School of Engineering to Expand Handwritten Text Recognition

University of Connecticut: UConn Library, School of Engineering to Expand Handwritten Text Recognition. “The UConn Library and the School of Engineering are working to develop new technology that applies machine learning to handwriting text recognition that will allow researchers to have improved access to handwritten historic documents. Handwritten documents are essential for researchers, but are often inaccessible because they are unable to be searched even after they are digitized. The Connecticut Digital Archive, a project of the UConn Library, is working to change that with a $24,277 grant awarded through the Catalyst Fund of LYRASIS, a nonprofit organization that supports access to academic, scientific, and cultural heritage.”

NIWA: The week it snowed everywhere

NIWA: The week it snowed everywhere. “NIWA and Microsoft Corp. are teaming up to make artificial intelligence handwriting recognition more accurate and efficient in a project that will support climate research. The project aims to develop better training sets for handwriting recognition technology that will ‘read’ old weather logs. The first step is to use weather information recorded during a week in July 1939 when it snowed all over New Zealand, including at Cape Reinga.”

The Washington Post: The National Archives has billions of handwritten documents. With cursive skills declining, how will we read them?

The Washington Post: The National Archives has billions of handwritten documents. With cursive skills declining, how will we read them?. “We all know that cursive has gone out of style. To modern young people, deciphering the wavy old-fashioned script can seem as relevant as dialing a rotary phone or milking a cow. For institutions like the National Archives, this poses a very specific problem.”

Student project report: Scribal Handwriting: An automated manuscript analysis tool (British Library)

British Library: Student project report: Scribal Handwriting: An automated manuscript analysis tool. “The team was challenged to create a tool for palaeographers (researchers who analyse handwriting) that can determine the date of a manuscript and sometimes even its scribe and place of production. To help with this task, we designed a tool to quickly find occurrences of similar handwritten characters across a collection of documents. This would be a lengthy and repetitive task if done manually by researchers. Typically, researchers compare characters’ features such as script, size and ink of different manuscripts to establish possible similarities between manuscripts and scribes. Our mission was to create a faster and reliable tool that could be used by palaeographers. Our aim was to speed up their research process by automating the comparisons between characters.”

Atlas Obscura: Where Old, Unreadable Documents Go to Be Understood

Atlas Obscura: Where Old, Unreadable Documents Go to Be Understood. “ON ANY GIVEN DAY, FROM her home on the Isle of Man, Linda Watson might be reading a handwritten letter from one Confederate soldier to another, or a list of convicts transported to Australia. Or perhaps she is reading a will, a brief from a long-forgotten legal case, an original Jane Austen manuscript. Whatever is in them, these documents made their way to her because they have one thing in common: They’re close to impossible to read.”