Search Results for "handwritten"
Sort By:
Showing 20 open source projects for "handwritten"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
1
SimpleHTR
Handwritten Text Recognition (HTR) system implemented with TensorFlow
...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. -
2
DeepSeek-OCR
Contexts Optical Compression
...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. It supports local deployment, enabling organizations concerned about privacy or latency to run the pipeline on-premises rather than send sensitive documents to third-party cloud services. The codebase is written in Python with a focus on modularity: you can swap preprocessing, recognition, and post-processing components as needed for custom workflows. -
3
HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
...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. HunyuanOCR handles complex documents: multi-column layouts, tables, mathematical formulas, mixed languages, handwritten or stylized fonts, receipts, tickets, and even video-frame subtitles. The project provides code, pretrained weights, and inference instructions, making it feasible to deploy locally or on a server, and to integrate with applications. -
4
MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
MiniSom is a minimalistic and Numpy-based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial Neural Network able to convert complex, nonlinear statistical relationships between high-dimensional data items into simple geometric relationships on a low-dimensional display. Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation of... -
Application Monitoring That Won't Slow Your App DownFull APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
-
5
Andrew NG Notes Collection
This is Andrew NG Coursera Handwritten Notes
Andrew-NG-Notes is a repository that provides comprehensive study notes for Andrew Ng’s widely known machine learning course. The project summarizes the key topics covered in the course, including supervised learning, neural networks, optimization algorithms, and model evaluation techniques. The notes aim to simplify complex mathematical explanations by organizing concepts into clear sections with diagrams, formulas, and concise descriptions. Each chapter mirrors the structure of the course... -
6
Chandra
OCR model for complex documents with layout-aware structured outputs
Chandra is an advanced OCR model designed to extract and structure information from complex documents such as tables, forms, handwritten notes, and mathematical content. It focuses on preserving full document layout, meaning that extracted text is accompanied by positional metadata like bounding boxes for each element. Chandra supports multiple output formats including Markdown, HTML, and JSON, making it suitable for downstream processing and integration into data pipelines. -
7
deepdoctection
A Repo For Document AI
DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for... -
8
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... -
9
Fashion-MNIST
A MNIST-like fashion product database
...Because the dataset represents real-world objects rather than handwritten digits, it offers a more challenging benchmark for testing machine learning algorithms. -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
-
10
Machine-Learning-Notes
Zhou Zhihua's "Machine Learning" push notes
The Machine-Learning-Notes repository contains detailed handwritten-style study notes based on the popular machine learning textbook by Zhou Zhihua. The project focuses on deriving formulas and explaining algorithms step by step so that learners can understand the mathematical foundations behind machine learning methods. The notes span sixteen chapters that cover a wide range of topics, including model evaluation, linear models, decision trees, neural networks, support vector machines, Bayesian classifiers, ensemble methods, clustering, dimensionality reduction, and reinforcement learning. ... -
11
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.
-
12
BPL
Bayesian Program Learning model for one-shot learning
BPL (Bayesian Program Learning) is a MATLAB implementation of the Bayesian Program Learning framework for one-shot concept learning (especially on handwritten characters). The approach treats each concept (e.g. a character) as being generated by a probabilistic program (motor primitives, strokes, spatial relationships), and inference proceeds by fitting those generative programs to a single example, generalizing to new examples, and generating new exemplars. The repository contains code for parsing stroke sequences, fitting motor programs, exemplar generation, classification, re-fitting, and demonstration scripts. -
13
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.
-
14
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.
-
15
Brainiac, Is C/C++ Libraries, Programs, And Python, And Lua Scripts For Neural Networking And Genetic Programming, In An Attempt To Create A "Glue-It-All-Together" Project, Striving Towards General Artificial Intelligence
-
16
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.
-
17
Akshara Malayalam OCR is a project for the development of an OCR for printed and handwritten documents in Malayalam language. The inspiration is from similar OCR softwares in other languages etc.
-
18
Classnotes is an OCR intended to translate handwritten scans into text. In order for the program to translate the scans the user must create a handwriting profile by training the OCR with scans.
-
19
...Intended for programs that need a simple neural network and do not want needlessly complex neural network libraries. Includes example application that trains a network to recognize handwritten digits.
-
20
Primary goal of Imated is development of handwritten/machine printed - OCR system. And second goal is development text editor, that will be in a position to import scanned documents OCR them on-the-fly, edit them and print/save as a picture again.
- Previous
- You're on page 1
- Next
