A Comprehensive Benchmark of Deep Learning Libraries on Mobile Devices-Reference-Cited by-同舟云学术

A Comprehensive Benchmark of Deep Learning Libraries on Mobile Devices

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2022
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Author:

Zhang Qiyang¹,Li Xiang²,Che Xiangying¹,Ma Xiao¹,Zhou Ao¹,Xu Mengwei¹,Wang Shangguang¹,Ma Yun³,Liu Xuanzhe³

Affiliation:

1. Beijing University of Posts and Telecommunications, China

2. China University of Petroleum, China

3. Peking University, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3485447.3512148

Reference84 articles.

1. [n.d.]. Performance measurement | TensorFlow Lite. https://www.tensorflow.org/lite/performance/measurement. https://www.tensorflow.org/lite/performance/measurement?hl=zh-cn [n.d.]. Performance measurement | TensorFlow Lite. https://www.tensorflow.org/lite/performance/measurement. https://www.tensorflow.org/lite/performance/measurement?hl=zh-cn

2. 2017. Snapdragon SNPE deep learning framework.https://developer.qualcomm.com/sites/default/files/docs/snpe/overview.html. 2017. Snapdragon SNPE deep learning framework.https://developer.qualcomm.com/sites/default/files/docs/snpe/overview.html.

3. 2017. XiaoMi Mace deep learning framework.https://github.com/XiaoMi/mace. 2017. XiaoMi Mace deep learning framework.https://github.com/XiaoMi/mace.

4. 2018. Tencent ncnn deep learning framework.https://github.com/Tencent/ncnn. 2018. Tencent ncnn deep learning framework.https://github.com/Tencent/ncnn.

5. 2019. Alibaba MNN deep learning framework.https://github.com/alibaba/MNN. 2019. Alibaba MNN deep learning framework.https://github.com/alibaba/MNN.

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