Low-Power Computer Vision: Status, Challenges, and Opportunities-Reference-Cited by-同舟云学术

Low-Power Computer Vision: Status, Challenges, and Opportunities

Published:2019-06 Issue:2 Volume:9 Page:411-421
ISSN:2156-3357
Container-title:IEEE Journal on Emerging and Selected Topics in Circuits and Systems
language:
Short-container-title:IEEE J. Emerg. Sel. Topics Circuits Syst.

Author:

Alyamkin Sergei,Ardi Matthew,Berg Alexander C.,Brighton Achille,Chen Bo,Chen Yiran^ORCID,Cheng Hsin-Pai,Fan Zichen^ORCID,Feng Chen,Fu Bo,Gauen Kent,Goel Abhinav^ORCID,Goncharenko Alexander,Guo Xuyang,Ha Soonhoi^ORCID,Howard Andrew,Hu Xiao^ORCID,Huang Yuanjun^ORCID,Kang Donghyun,Kim Jaeyoun^ORCID,Ko Jong Gook,Kondratyev Alexander,Lee Junhyeok^ORCID,Lee Seungjae,Lee Suwoong,Li Zichao,Liang Zhiyu,Liu Juzheng,Liu Xin,Lu Yang,Lu Yung-Hsiang^ORCID,Malik Deeptanshu,Nguyen Hong Hanh^ORCID,Park Eunbyung,Repin Denis,Shen Liang,Sheng Tao,Sun Fei,Svitov David,Thiruvathukal George K.,Zhang Baiwu^ORCID,Zhang Jingchi,Zhang Xiaopeng,Zhuo Shaojie

Funder

IEEE Rebooting Computing of the IEEE Annual International Low-Power Image Recognition Challenge

Google

Facebook

Nvidia

Xilinx

MediaTek

IEEE Circuits and Systems Society

IEEE Council on Electronic Design Automation

IEEE Green ICT

IEEE Council on Superconductivity

Electronics and Telecommunications Research Institute

Korean Government through the Object Information Extraction and Real-to-Virtual Mapping Based AR Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/5503868/8734723/08693826.pdf?arnumber=8693826

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