Projects that are tagged with image processing.


Logo ADAMS 0.4.4

by fracpete - October 25, 2013, 04:10:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4519 views, 1041 downloads, 1 subscription

About: The Advanced Data mining And Machine learning System (ADAMS) is a novel, flexible workflow engine aimed at quickly building and maintaining real-world, complex knowledge workflows.

Changes:
  • Added 30 more conversions and 70 more actors
  • new timeseries module, includes Weka's Forecasting plugin
  • OCR support using TesseractOCR wrapper
  • extended JSON support (value extraction using JSON path)
  • support for processing XML/HTML (DOM generation, XSLT, XPath)
  • SQL-like query language for spreadsheets
  • generic support Java properties files (read/write/modify)
  • generic serialization support
  • support for sequence plotter overlays
  • basic WebServer capability (using Jetty)
  • CSV file reader/writer now support file encodings (eg UTF-8, UTF-16)

Logo Pattern Recognition for Neuroimaging Toolbox v1.1

by chrisp - September 16, 2013, 23:19:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 878 views, 154 downloads, 1 subscription

About: PRoNTo is freely available software and aims to facilitate the interaction between the neuroimaging and machine learning communities. The toolbox is based on pattern recognition techniques for the analysis of neuroimaging data. PRoNTo supports the analysis of all image modalities as long as they are NIfTI format files. However, only the following modalites have been tested for version 1.1: sMRI, fMRI, PET, FA (fractional anisotropy) and Beta (GLM coefficients) images.

Changes:

Initial Announcement on mloss.org.


Logo Local Binary Pattern 1.0.0

by openpr_nlpr - December 2, 2011, 05:33:44 CET [ Project Homepage BibTeX Download ] 1208 views, 387 downloads, 1 subscription

About: This is a class to calculate histogram of LBP (local binary patterns) from an input image, histograms of LBP-TOP (local binary patterns on three orthogonal planes) from an image sequence, histogram of the rotation invariant VLBP (volume local binary patterns) or uniform rotation invariant VLBP from an image sequence.

Changes:

Initial Announcement on mloss.org.