Area-efficient FPGA implementation of minimalistic convolutional neural network using residue number system
Convolutional Neural Networks (CNN) is the promising tool for solving task of image recognition in computer vision systems. However, the most known implementation of CNNs require a significant amount of memory for storing weights in training and work. To reduce the resource costs of CNN implementati...
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| Hoofdauteurs: | , , , , , , , |
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| Formaat: | Статья |
| Taal: | English |
| Gepubliceerd in: |
IEEE Computer Society
2019
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| Onderwerpen: | |
| Online toegang: | https://www.scopus.com/record/display.uri?eid=2-s2.0-85061049082&origin=resultslist&sort=plf-f&src=s&st1=%09Area-Efficient+FPGA+Implementation+of+Minimalistic+Convolutional+Neural+Network+Using+Residue+Number+System&st2=&sid=5de745aaf0b399b11edbcdbf364e241e&sot=b&sdt=b&sl=123&s=TITLE-ABS-KEY%28%09Area-Efficient+FPGA+Implementation+of+Minimalistic+Convolutional+Neural+Network+Using+Residue+Number+System%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru/handle/20.500.12258/4353 |
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