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---
license: mit
datasets:
- ILSVRC/imagenet-1k
pipeline_tag: image-classification
---
# Introduction
This repository stores the model for Squeezenet, compatible with Kalray's neural network API. </br>
Please see www.github.com/kalray/kann-models-zoo for details and proper usage. </br>
# 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: nbouberbachene@kalrayinc.com |