Complexity-Aware Layer-Wise Mixed-Precision Schemes With SQNR-Based Fast Analysis
Author:
Affiliation:
1. Department of Electronic and Electrical Engineering, Ewha Womans University, Seoul, Republic of Korea
2. OPENEDGES Technology, Inc., Seoul, Republic of Korea
Funder
Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (Ministry of Science, ICT
Variable-precision deep learning processor technology for high-speed multiple object tracking
National Research Foundation (NRF), Korea
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10287357.pdf?arnumber=10287357
Reference47 articles.
1. A survey on deep learning and its applications
2. Mixed precision training of convolutional neural networks using integer operations;das;arXiv 1802 00930,2018
3. A survey of modern deep learning based object detection models
4. HAQ: Hardware-Aware Automated Quantization With Mixed Precision
5. Rethinking the value of network pruning;liu;arXiv 1810 05270,2018
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