FiGO: Fine-Grained Query Optimization in Video Analytics-Reference-Cited by-同舟云学术

FiGO: Fine-Grained Query Optimization in Video Analytics

Published:2022-06-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 International Conference on Management of Data
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Author:

Cao Jiashen¹,Sarkar Karan¹,Hadidi Ramyad¹,Arulraj Joy¹,Kim Hyesoon¹

Affiliation:

1. Georgia Institute of Technology, Atlanta, GA, USA

Funder

Institute of Information & Communications Technology Planning & Evaluation (IITP)

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3514221.3517857

Reference34 articles.

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3. Favyen Bastani , Songtao He , Arjun Balasingam , Karthik Gopalakrishnan , Mohammad Alizadeh , Hari Balakrishnan , Michael Cafarella , Tim Kraska , and Sam Madden . 2020 . MIRIS : Fast Object Track Queries in Video. In SIGMOD. 1907--1921. Favyen Bastani, Songtao He, Arjun Balasingam, Karthik Gopalakrishnan, Mohammad Alizadeh, Hari Balakrishnan, Michael Cafarella, Tim Kraska, and Sam Madden. 2020. MIRIS : Fast Object Track Queries in Video. In SIGMOD. 1907--1921.

4. Christopher Canel Thomas Kim Giulio Zhou Conglong Li Hyeontaek Lim David G Andersen Michael Kaminsky and Subramanya R Dulloor. 2019. Scaling Video Analytics on Constrained Edge Nodes. In SysML. Christopher Canel Thomas Kim Giulio Zhou Conglong Li Hyeontaek Lim David G Andersen Michael Kaminsky and Subramanya R Dulloor. 2019. Scaling Video Analytics on Constrained Edge Nodes. In SysML.

5. Olivier Chapelle and Lihong Li. 2011. An Empirical Evaluation of Thompson Sampling. In NeurIPS. Olivier Chapelle and Lihong Li. 2011. An Empirical Evaluation of Thompson Sampling. In NeurIPS.

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