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Understanding error propagation in deep learning neural network (DNN) accelerators and applications

Overview of attention for article published in this source, November 2017
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257 Mendeley
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Article details
Title
Understanding error propagation in deep learning neural network (DNN) accelerators and applications
Published by
Association for Computing Machinery (ACM), November 2017
DOI 10.1145/3126908.3126964
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 257 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 257 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 68 26%
Student > Master 28 11%
Researcher 17 7%
Student > Doctoral Student 12 5%
Student > Bachelor 11 4%
Other 27 11%
Unknown 94 37%
Readers by discipline
Readers by discipline Count As %
Computer Science 79 31%
Engineering 62 24%
Business, Management and Accounting 5 2%
Social Sciences 4 2%
Design 2 <1%
Other 13 5%
Unknown 92 36%