@inproceedings{fa155c14ec2147b6a007fa12ff4a08ae,
title = "A classification centric quantizer for efficient encoding of predictive feature errors",
abstract = "We design a joint compression and classification system that optimizes visual fidelity and classification accuracy under a bit rate constraint. We propose a classification centric quantizer (CCQ) whose parameters are learned from labeled training data. We apply and evaluate the CCQ on a scene classification problem and compare the results to previous work.",
author = "{Deeann Chen}, Scott and Pierre Moulin",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 ; Conference date: 02-11-2014 Through 05-11-2014",
year = "2015",
month = apr,
day = "24",
doi = "10.1109/ACSSC.2014.7094844",
language = "English (US)",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
publisher = "IEEE Computer Society",
pages = "2098--2102",
editor = "Matthews, {Michael B.}",
booktitle = "Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers",
}