ELIχR: Eliminating Computation Redundancy in CNN-Based Video Processing | NSF Public Access Repository

skip to main content

An official website of the United States government Here's how you know

Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Citation Details

ELIχR: Eliminating Computation Redundancy in CNN-Based Video Processing

Award ID(s):: 1750760 2018910

PAR ID:: 10323450

Author(s) / Creator(s):: Schmerge, Jordan; Mawhirter, Daniel; Holmes, Connor; McClurg, Jedidiah; Wu, Bo

Date Published:: 2021-11-01

Journal Name:: IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop

Page Range / eLocation ID:: 34 to 44

Format(s):: Medium: X

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
Accepted Manuscript
Conference Paper:
https://doi.org/10.1109/RSDHA54838.2021.00010