Search Results for "handwritten recognition"
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Showing 16 open source projects for "handwritten recognition"
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Comet Backup - Fast, Secure Backup Software for MSPsComet is a flexible backup platform, giving you total control over your backup environment and storage destinations.
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Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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SimpleHTR
Handwritten Text Recognition (HTR) system implemented with TensorFlow
...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. -
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DeepSeek-OCR
Contexts Optical Compression
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. ... -
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HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a wide variety of OCR tasks, outperforming many traditional OCR systems and even other multimodal models on benchmark suites. ... -
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Knet
Koç University deep learning framework
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... -
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SYSU-OpenEdgeAI
A public account displaying works from SYSU-OpenEdgeAI Club
...All of our works are open source, and we sincerely welcome all the Edge AI lovers to join us to solve problems and learn! Until 2020-12-27, we have already upload three projects: 1. ov_carplate.zip is a car plate recognition project based on Zedboard Zynq-7000. 2. mnist_hls.zip is a realization of Lenet for MNIST handwritten digit recognition using Vivado hls tool. 3. rapidlayout.zip is an end-to-end hard block placement and routing flow for systolic accelerators on FPGA, RapidLayout. It is the sourcecode of our paper:https://ieeexplore.ieee.org/document/9221566 . ... -
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Tensorflow and deep learning
A crash course in six episodes for software developers
...The repository covers core neural network concepts such as weights, biases, activation functions, and gradient descent, as well as more advanced techniques like convolutional networks, recurrent networks, and reinforcement learning. It includes multiple hands-on projects, such as handwritten digit recognition, airplane detection in images, and text generation using recurrent neural networks, which demonstrate how different architectures solve real-world problems. -
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updownreader
Open source program for efficiently processing 50% von Frey thresholds
The UpDown Reader software allows for the efficient processing of 50% von Frey thresholds based on the up-down method for 2 species (mouse, rat) and 2 forms of stimulus (plantar, visceral). Templates for each species are provided along with the application. Given a PDF input, the software identifies and extracts the grid of von Frey assessment tables, recognizes the handwritten sequences entered in each of them, and computes the 50% response thresholds according to the selected species... -
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QJDicExample
QJDicExample is an English <-> Japanese dictionary.
QJDicExample is an Japanese to English and English to Japanese dictionary featuring words/names/kanji/sentences search. QJDicExample uses JMdict, JMnedict, Kanjidic2, Radkfilex, KanjiVG, Tanaka Corpus / Tatoeba databases for translations and zinnia recognition library for handwritten kanji recognition. Latest source code: git clone git://git.code.sf.net/p/qjdicexample/code qjdicexample-code -
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MHW
DATABASE OF HANDWRITTEN MONGOLIAN WORDS
...The testing set II of MHW database consists of 939 words; each word is written 15 times written by 50 different writers with training set. The words in training and testing set have a few intersections. It is designed for training and testing recognition systems for handwritten Mongolian words. The MHW-database is available for the purpose of research. usage instructions given at https://sourceforge.net/p/mongolian-hw/wiki/Home/ -
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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.
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1¢ Recognizer
A simple, efficient, and accurate gesture recognizer
The One Cent Recognizer is an easy-to-implement, efficient, and accurate handwritten gesture recognizer. If you would like to cite One Cent in a publication please use: J. Herold and T.F. Stahovich: The 1¢ Recognizer: A Fast, Accurate, and Eas y-to-Implement Handwritten Gesture Recognition Technique. In Proceedings of the 9th Eurographics workshop on Sketch-based interfaces and modeling (New York, NY, USA, 2012), SBIM '12, ACM -
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The AK toolkit is another kit for building and use Hidden Markov Models (HMMs). Originally developed for handwritten text recognition (HTR) using Bernoulli HMMs, it also implements diagonal Gaussians and can be used for any other purpose.
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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.
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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.
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