Search Results for "11"

...Karunananda, G. Rzevski, Multi-agent solution for managing complexity in English to Sinhala Machine Translation, International Journal of Design & Nature and Ecodynamics, Volume 11, Issue 2, 2016, 88 – 96. B. Hettige, A. S. Karunananda, G. Rzevski, ” MaSMT: A Multi-agent System Development Framework for English-Sinhala Machine Translation”, International Journal of Computational Linguistics and Natural Language Processing (IJCLNLP), Volume 2 Issue 7 July 2013.

Brood War Easy Map is a C++ library that analyses Brood War's maps and provides relevant information such as areas, choke points and base locations. It is built on top of the BWAPI library. It first aims at simplifying the development of bots for Brood War, but can be used for any task requiring high level map information. It can be used as a replacement for the BWTA2 add-on, as it performs faster and shows better robustness while providing similar information.

libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.

This site contains four packages of Mass and mass-based density estimation. 1. The first package is about the basic mass estimation (including one-dimensional mass estimation and Half-Space Tree based multi-dimensional mass estimation). This packages contains the necessary codes to run on MATLAB. 2. The second package includes source and object files of DEMass-DBSCAN to be used with the WEKA system. 3. The third package DEMassBayes includes the source and object files of a Bayesian...

Mocapy++ is a Dynamic Bayesian Network toolkit, implemented in C++. It supports discrete, multinomial, Gaussian, Kent, Von Mises and Poisson nodes. Inference and learning is done by Gibbs sampling/Stochastic-EM.

...It incorporates both text and layout (position) features to effectively process structured documents like forms, invoices, and receipts. This base version has 113 million parameters and is pre-trained on 11 million documents from the IIT-CDIP dataset. LayoutLM enables better performance in tasks where the spatial arrangement of text plays a crucial role. The model uses a standard BERT-like architecture but enriches input with 2D positional embeddings. It achieves state-of-the-art results in form understanding and information extraction benchmarks. ...