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CN24 Convolutional Neural Networks for Semantic Segmentation 1.0
by erik - February 23, 2015, 09:02:06 CET [
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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?
- Designed for pixel-wise labeling and semantic segmentation (train and test your own networks!)
- Suited for various applications in driver assistance systems, scene understanding, remote sensing, biomedical image processing and many more
- OpenCL support not only suited for NVIDIA GPUs
- 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
- 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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Project details for CN24 Convolutional Neural Networks for Semantic Segmentation
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Details
- Version:
- 1.0
- Submitter:
- erik
- Author(s):
- Clemens Alexander Brust , Sven Sickert , Marcel Simon , Erik Rodner
- Posted:
- 23 February 2015
- Last Updated:
- 23 February 2015
- Open Source License:
- bsd 3 clause license
- Programming Language(s):
- c++