2020
DOI: 10.1007/s10836-020-05879-0
|View full text |Cite
|
Sign up to set email alerts
|

High Performance Approximate Memories for Image Processing Applications

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 26 publications
0
1
0
Order By: Relevance
“…The approximation benefits depend on the accuracy requirements of the application results that usually rely on the acceptance of a well-defined statistical behavior of the computational outcome [94]. Approximation techniques have been applied to several contexts, including wireless sensor networks [3], Internet of Things (IoT) for health monitoring [41], Deep Neural Networks (DNN) [61], and image processing [54].…”
Section: Background and Related Workmentioning
confidence: 99%
“…The approximation benefits depend on the accuracy requirements of the application results that usually rely on the acceptance of a well-defined statistical behavior of the computational outcome [94]. Approximation techniques have been applied to several contexts, including wireless sensor networks [3], Internet of Things (IoT) for health monitoring [41], Deep Neural Networks (DNN) [61], and image processing [54].…”
Section: Background and Related Workmentioning
confidence: 99%