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Copyright Pohang University of Science and Technology. All rights reserved.
Contact persons:
Hyeonowo Noh (hyeonwoonoh_ <at> postech.ac.kr)
This software is being made available for individual research use only.
Any commercial use or redistribution of this software requires a license from
the Pohang University of Science and Technology.
You may use this work subject to the following conditions:
1. This work is provided "as is" by the copyright holder, with
absolutely no warranties of correctness, fitness, intellectual property
ownership, or anything else whatsoever. You use the work
entirely at your own risk. The copyright holder will not be liable for
any legal damages whatsoever connected with the use of this work.
2. The copyright holder retain all copyright to the work. All copies of
the work and all works derived from it must contain (1) this copyright
notice, and (2) additional notices describing the content, dates and
copyright holder of modifications or additions made to the work, if
any, including distribution and use conditions and intellectual property
claims. Derived works must be clearly distinguished from the original
work, both by name and by the prominent inclusion of explicit
descriptions of overlaps and differences.
3. The names and trademarks of the copyright holder may not be used in
advertising or publicity related to this work without specific prior
written permission.
4. In return for the free use of this work, you are requested, but not
legally required, to do the following:
* If you become aware of factors that may significantly affect other
users of the work, for example major bugs or
deficiencies or possible intellectual property issues, you are
requested to report them to the copyright holder, if possible
including redistributable fixes or workarounds.
* If you use the work in scientific research or as part of a larger
software system, you are requested to cite the use in any related
publications or technical documentation. The work is based upon:
Hyeonwoo Noh, Seunghoon Hong, Bohyung Han.
Learning Deconvolution Network for Semantic Segmentation
arXiv:1505.04366, 2015.
@article{noh2015learning,
title={Learning Deconvolution Network for Semantic Segmentation},
author={Noh, Hyeonwoo and Hong, Seunghoon and Han, Bohyung},
journal={arXiv preprint arXiv:1505.04366},
year={2015}
}
This copyright notice must be retained with all copies of the software,
including any modified or derived versions.