Project details for CN24 Convolutional Neural Networks for Semantic Segmentation

Logo CN24 Convolutional Neural Networks for Semantic Segmentation 1.0

by erik - February 23, 2015, 09:02:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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Description:

CN24 is a complete semantic segmentation framework using fully convolutional networks. It supports a wide variety of platforms (Linux, Mac OS X and Windows) and libraries (OpenCL, Intel MKL, AMD ACML...) while providing dependency-free reference implementations. The software is developed at the Computer Vision Group, University of Jena.

Why should I use CN24?

  1. Designed for pixel-wise labeling and semantic segmentation (train and test your own networks!)
  2. Suited for various applications in driver assistance systems, scene understanding, remote sensing, biomedical image processing and many more
  3. OpenCL support not only suited for NVIDIA GPUs
  4. High-performance implementation with minimal dependencies to other libraries
Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
URL: Project Homepage
Supported Operating Systems: Linux, Macosx, Windows
Data Formats: Any
Tags: Deep Learning, Segmentation, Convolutional Neural Networks, Computer Vision, Pixelwise Labeling
Archive: download here

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