14.1 A 2.9TOPS/W deep convolutional neural network SoC in FD-SOI 28nm for intelligent embedded systems

@article{Desoli2017141A2,
  title={14.1 A 2.9TOPS/W deep convolutional neural network SoC in FD-SOI 28nm for intelligent embedded systems},
  author={Giuseppe Desoli and Nitin Chawla and Thomas Boesch and Surinder-pal Singh and Elio Guidetti and Fabio De Ambroggi and Tommaso Majo and Paolo Zambotti and Manuj Ayodhyawasi and Harvinder Singh and Nalin Aggarwal},
  journal={2017 IEEE International Solid-State Circuits Conference (ISSCC)},
  year={2017},
  pages={238-239}
}
A booming number of computer vision, speech recognition, and signal processing applications, are increasingly benefiting from the use of deep convolutional neural networks (DCNN) stemming from the seminal work of Y. LeCun et al. [1] and others that led to winning the 2012 ImageNet Large Scale Visual Recognition Challenge with AlexNet [2], a DCNN significantly outperforming classical approaches for the first time. In order to deploy these technologies in mobile and wearable devices, hardware… CONTINUE READING

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