I came across https://www.hyperscience.com/forms where they demonstrate the ability to recognize handwritten text. I am interested in learning from folks in the deep learning field who know more than I do as to what techniques/resources are out there for me to train a network to recognize handwritten text?
You’ll need to be familiar with pretty much all the material covered in parts 1 & 2 of the course to build such a system, since it incorporates language modeling, segmentation, object localization, classification, etc. You can get some ideas from the ICDAR handwriting competition entries: http://u-pat.org/ICDAR2017/program_competitions.php
Hello Jeremy, I am also very much interested in doing this handwriting recognition project but have few questions regarding this. What if I have an image only of one or two words in it, would I need a object localization for that? Also I am a bit confused about how to move forward with a training dataset, what dataset should I use for this ?
Because from what i have at the moment is a dataset which has all the letters Caps and small and the digits (0-9) in different folders. What my concern is, while training on this kind of dataset it would train on images only of a particular alphabet or a number but when it receives an image of a complete word, how would it go forward with this? Do we need a sliding window or something in this case?
You might want to check out this project: https://transkribus.eu/Transkribus/ This does have pre-trained models which can then be fine-tuned on a specific handwriting, could be a particular language but also a particular person.