Kalray / squeezenet

Introduction

This repository stores the model for Squeezenet, compatible with Kalray's neural network API.
Please see www.github.com/kalray/kann-models-zoo for details and proper usage.

Contents

• ONNX: squeezenet-v1.onnx

Lecture note reference

• https://arxiv.org/pdf/1602.07360

Repository or links references

• https://github.com/onnx/models/blob/5faef4c33eba0395177850e1e31c4a6a9e634c82/vision/classification/squeezenet/model/squeezenet1.0-12.onnx

BibTeX entry and citation info

@article{DBLP:journals/corr/IandolaMAHDK16,
  author       = {Forrest N. Iandola and
                  Matthew W. Moskewicz and
                  Khalid Ashraf and
                  Song Han and
                  William J. Dally and
                  Kurt Keutzer},
  title        = {SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and {\textless}1MB
                  model size},
  journal      = {CoRR},
  volume       = {abs/1602.07360},
  year         = {2016},
  url          = {http://arxiv.org/abs/1602.07360},
  eprinttype    = {arXiv},
  eprint       = {1602.07360},
  timestamp    = {Fri, 20 Nov 2020 16:16:06 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/IandolaMAHDK16.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

Author: [email protected]