Search Results for "handwriting recognition source code"

Introduction NLP is a Chinese-language study-notes repository based on the book Introduction to Natural Language Processing by the author of HanLP. It explains NLP concepts in accessible language while pairing theory with practical implementation notes. The material begins with basic concepts and Chinese word segmentation before progressing into statistical sequence models. Later chapters cover part-of-speech tagging, named entity recognition, information extraction, text clustering, text...

latexify_py converts small, math-heavy pieces of Python code into human-readable LaTeX that mirrors the intent of the computation, not just its surface syntax. It parses Python functions and expressions into an abstract syntax tree (AST), applies symbolic rewrites for common mathematical constructs, and then emits LaTeX that compiles cleanly in standard environments. Typical use cases include turning analytical utilities—like probability mass functions, activation formulas, or recurrence...

Neural Networks and Deep Learning is an open-source collection of Python code examples accompanying Michael Nielsen's educational book of the same name. It helps students, researchers, and developers understand how neural networks function through practical implementations. The project demonstrates fundamental concepts such as feedforward networks, stochastic gradient descent, backpropagation, and neural network training. Its examples include recognizing handwritten digits using the MNIST...

libVMR is a class library written in Java which implements code generator for group method of data handling - GMDH. The library is intended for users, with machine learning skills. libVMR provides an effective framework for the research and development of data mining and predictive analytics. libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from...

..., WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer Vision and Pattern Recognition, 2012. This source code is provided without warranty and is available under the GPL license. More commercially-friendly licenses may be available. Please contact Stephen O'Hara for license options. Please view the wiki on this site for installation instructions and examples on reproducing the results of the papers.

Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.