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LICENSE
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Copyright (c) <2019>
<Nankai University, Tianjin, China>
<Advanced Digital Sciences Center, Singapore>
<University of Illinois at Urbana-Champaign>
All rights reserved.
General terms and conditions for use of the Quantization-caffe software package.
The open-source package comprising "Quantization-caffe" software and the provided
documentation is copyright protected.
The copyright is owned by Cheng Gong, Ye Lu, Tao Li, Yao Chen, Deming Chen, Nankai
University, China, Advanced Digital Sciences Center, Singapore, and University of
Illinois at Urbana-Champaign, USA.
General terms and conditions for use of the T-DLA software. The software
comprising "T-DLA" and the documentation provided with them are
copyright Yao Chen, Deming Chen, the Advanced Digital Sciences Center, Singapore
and the University of Illinois at Urbana-Champaign.
Only non-commercial, not-for-profit use of this software is permitted. No part
of this software may be incorporated into a commercial product without the
written consent of the authors. Similarly, use of
this software to assist in the development of new commercial applications is
prohibited, unless the written consent of the authors is obtained.
This software is provided "as is" with no warranties or guarantees of support.
All users of the software must take the copy from this site. You may modify or
use the source code for other non-commercial, not-for-profit research endeavours,
provided that all copyright attribution on the source code is retained, and the
original or modified source code is not redistributed, in whole or in part, or
included in or with any commercial product, except by written agreement with
the authors, and full and complete attribution for use of the code is given in
any resulting publications. Subject to these conditions, the software is
provided free of charge to all interested parties.
When referencing this particular open-source software in a publication, please
cite the following publication:
Cheng Gong, Ye Lu, Tao Li, Xiaofan Zhang, Cong Hao, Deming Chen and Yao Chen,
"uL2Q: An Ultra-low Loss Quantization Method for DNN", The 2019 International
Joint Conference on Neural Networks (IJCNN).
Yao Chen, Kai Zhang, Cheng Gong, Cong Hao, Xiaofan Zhang, Tao Li and Deming Chen,
"T-DLA: An Open-source Deep Learning Accelerator for Ternarized DNN Models on Embedded FPGA",
IEEE Computer Society Annual Symposium on VLSI 2019 (ISVLSI)