Marginalia and machine learning (Pytorch)
For the detection of text written in document margins or handwritten notes, we have a PyTorch implementation of a Handwritten Text Recognition (HTR) system that focuses on automatic detection and recognition of handwritten marginalia texts. Faster R-CNN network is used for detection of marginalia and AttentionHTR is used for word recognition. The data comes from early book collections (printed) found in the Uppsala University Library, with handwritten marginalia texts.Source code and pre-trained models are available at Github.This is a work under progress.
The SSH Open Marketplace is maintained and will be further developed by three European Research Infrastructures - DARIAH, CLARIN and CESSDA - and their national partners. It was developed as part of the "Social Sciences and Humanities Open Cloud" SSHOC project, European Union's Horizon 2020 project call H2020-INFRAEOSC-04-2018, grant agreement #823782.
