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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/114924...
Part of book or chapter of book . 2005 . Peer-reviewed
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DBLP
Conference object . 2023
Data sources: DBLP
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Hardware-Accelerated Template Matching

Authors: Raúl Cabido; Antonio S. Montemayor; Ángel Sánchez 0001;

Hardware-Accelerated Template Matching

Abstract

In the last decade, consumer graphics cards have increased their power because of the computer games industry. These cards are now programmable and capable of processing huge amounts of data in a SIMD fashion. In this work, we propose an alternative implementation of a very intuitive and well known 2D template matching, where the most computationally expensive task is accomplished by the graphics hardware processor. This computation approach is not new, but in this work we resume the method step-by-step to better understand the underlying complexity. Experimental results show an extraordinary performance trade-off, even working with obsolete hardware.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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