Projects that are tagged with image processing.


Logo ADAMS 17.12.0

by fracpete - December 20, 2017, 09:38:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 34608 views, 6191 downloads, 3 subscriptions

About: The Advanced Data mining And Machine learning System (ADAMS) is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes.

Changes:

Some highlights:

  • Code base was moved to Github
  • Nearly 90 new actors, 25 new conversions
  • much improved deeplearning4j module
  • experimental support for Microsoft's CNTK deep learning framework
  • rsync module
  • MEKA webservice module
  • improved support for image annotations
  • improved LaTeX support
  • Websocket support

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 ] 5078 views, 1017 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 ] 4049 views, 1095 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.