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Embedded Deep Learning Algorithms, Architectures and Circuits for Always-on Neural Network Processing /

This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost...

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Detaylı Bibliyografya
Asıl Yazarlar: Moons, Bert (Yazar), Bankman, Daniel (Yazar), Verhelst, Marian (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edisyon:1st ed. 2019.
Konular:
Online Erişim:Full-text access
OPAC'ta görüntüle
İçindekiler:
  • Chapter 1 Embedded Deep Neural Networks
  • Chapter 2 Optimized Hierarchical Cascaded Processing
  • Chapter 3 Hardware-Algorithm Co-optimizations
  • Chapter 4 Circuit Techniques for Approximate Computing
  • Chapter 5 ENVISION: Energy-Scalable Sparse Convolutional Neural Network Processing
  • Chapter 6 BINAREYE: Digital and Mixed-signal Always-on Binary Neural Network Processing
  • Chapter 7 Conclusions, contributions and future work.