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Object‐oriented image analysis for very‐low‐bitrate video‐coding systems using the CNN universal machine — André Stoffels (1997) | RDL Network
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Object‐oriented image analysis for very‐low‐bitrate video‐coding systems using the CNN universal machine
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Leon O Chua
University of California, Berkeley
Object‐oriented image analysis for very‐low‐bitrate video‐coding systems using the CNN universal machine
Article
1997
en
Authors
AS
André Stoffels
TR
Tamás Roska
Leon O Chua
University of California, Berkeley
Abstract
1 min read
The CNN universal machine (CNNUM) is applied to object-oriented video compression and proves its universality for future applications in the field of very-low-bitrate coding. This proposal joins recent work of Venetianer and Roska in unfolding the enormous computational abilities of the CNNUM for a wide class of video compression techniques. Here a novel image analysis technique is considered and realized in the form of analogic CNN algorithms. The specific features of the scheme, among them the extensive use of dynamic (finite running time) CNN cloning templates, are outlined and discussed through different computer simulations. When implemented on the CNNUM, its performances outdo those of equivalent digital systems and qualify the CNNUM as a serious competitor for future video coding hardware. © 1997 John Wiley & Sons, Ltd.
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