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Author Kelliher, A.
Sponsorship IEEE Computer Society
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1994
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Natural sciences & mathematics ♦ Physics ♦ Electricity & electronics
Subject Keyword Motion pictures ♦ Media ♦ Art ♦ Visualization ♦ Artificial intelligence ♦ Digital art ♦ Machine vision ♦ visualization ♦ machine learning ♦ big data ♦ multimedia ♦ data analysis ♦ graphics
Abstract Recent interdisciplinary explorations, integrating computer science, math, the digital humanities, and the arts, point to the utilitarian and expressive capabilities of machine-learning approaches in creating work with diverse appeal. These initiatives include research within the relatively traditional domain of historical art analysis, a growing collection of body-tracking work using machine learning in the background, and a variety of provocative art installations that place algorithmic computing front and center. While these projects tackle their subject at varying levels of scale and depth and in different contexts, each contributes to building the public discourse about the impact, role, and reach of machine learning in our lives.
Description Author affiliation :: Carnegie Mellon Univ., Pittsburgh, PA, USA
ISSN 1070986X
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-01-01
Publisher Place U.S.A.
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Volume Number 22
Issue Number 2
Size (in Bytes) 5.28 MB
Page Count 5
Starting Page 18
Ending Page 22


Source: IEEE Xplore Digital Library