Corpus ID: 218630306

ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network

@article{Gschwend2020ZynqNetAF,
  title={ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network},
  author={David Gschwend},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.06892}
}
  • David Gschwend
  • Published 2020
  • Computer Science
  • ArXiv
  • Image Understanding is becoming a vital feature in ever more applications ranging from medical diagnostics to autonomous vehicles. Many applications demand for embedded solutions that integrate into existing systems with tight real-time and power constraints. Convolutional Neural Networks (CNNs) presently achieve record-breaking accuracies in all image understanding benchmarks, but have a very high computational complexity. Embedded CNNs thus call for small and efficient, yet very powerful… CONTINUE READING
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