Search Results for "handwritten recognition"

...It also employs connectionist temporal classification (CTC) to align predicted character sequences with input images without requiring character-level segmentation. The repository provides code for training models, performing inference on handwritten text images, and evaluating recognition accuracy. SimpleHTR is commonly used as an educational example for understanding how modern handwriting recognition systems operate.

DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body text, interpreting tables, or recognizing handwritten versus printed words. ...

Knet.jl is a deep learning package implemented in Julia, so you should be able to run it on any machine that can run Julia. It has been extensively tested on Linux machines with NVIDIA GPUs and CUDA libraries, and it has been reported to work on OSX and Windows. If you would like to try it on your own computer, please follow the instructions on Installation. If you would like to try working with a GPU and do not have access to one, take a look at Using Amazon AWS or Using Microsoft Azure. If...

This paper represent a development and deployment and/or Implementation of Optical Character Recognition (OCR) to translate images of typewritten or handwritten characters into electronically editable format by preserving font properties. OCR can do this by applying pattern matching algorithm. The Recognized characters are stored in editable format. Thus OCR make the computer read the printed documents discarding noise. Keywords- Optical Character Recognition, Image convert to character, Image cropping.

UCR is a project name for the development of an handwritten characters in Korean language. The goal is to create a UCR Library for handwriting as well as OCR from off-line, on-line data. And we have a plan to build a UCR library for mobile.

A handwritten number recognition system was developed by using image processing and neural network technique. The system was developed in Java. Other applications which make use of image processing and neural network technique will be published too.