Search Results for "a line"

...It supports a good range of image formats, including JPEG, JPEG2000, JPEG-XL, TIFF, PNG, WebP, HEIC, AVIF, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM / PGM / PFM, CSV, GIF, Analyze, NIfTI, DeepZoom, and OpenSlide. It can also load images via ImageMagick or GraphicsMagick, letting it work with formats like DICOM. It comes with bindings for C, C++, and the command-line. Full bindings are available for Ruby, Python, PHP, C# / .NET, Go, and Lua.

This is the proof-of-concept implementation of the FAUM Clustering method. This implementation was used to perform the published results and is now released in the hope that it will be useful.

One more lightweight neural network in C.

TexLexAn is an open source text analyser for Linux, able to estimate the readability and reading time, to classify and summarize texts. It has some learning abilities and accepts html, doc, pdf, ppt, odt and txt documents. Written in C and Python.

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.

MoMS (Model Management System) is a model management system for statistical models, a little bit like a database management system. Instead of having tables, we have models that can be updated and queried.

With miao3d you can train a specific Gaussian Markov Random Field (GMRF) that then can be used to estimate a depthmap ("3D"), given an image ("2D"). A GUI allows inspection of the image + depthmap.

The Naval Postgraduate School Machine Learning Library. There are no official releases yet, but you can pull from the mercurial repository. See the wiki for help: https://sourceforge.net/apps/mediawiki/npsml/index.php?title=Main_Page

...An important goal of Betelgeuse is to have a clean, professional user interface amenable to less technical users, and to have multiple user interfaces for graphical, command line, and remote server use.

A fast kernel density estimation based classifier. Uses multi resolution KD trees to significantly reduce the number of calculations needed to perform density estimation.