Min Li, Yu Li, Ye Tian, Li Jiang, Qiang Xu. AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference. In 58th ACM/IEEE Design Automation Conference, DAC 2021, San Francisco, CA, USA, December 5-9, 2021. pages 409-414, IEEE, 2021. [doi]
@inproceedings{LiLTJX21,
title = {AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference},
author = {Min Li and Yu Li and Ye Tian and Li Jiang and Qiang Xu},
year = {2021},
doi = {10.1109/DAC18074.2021.9586176},
url = {https://doi.org/10.1109/DAC18074.2021.9586176},
researchr = {https://researchr.org/publication/LiLTJX21},
cites = {0},
citedby = {0},
pages = {409-414},
booktitle = {58th ACM/IEEE Design Automation Conference, DAC 2021, San Francisco, CA, USA, December 5-9, 2021},
publisher = {IEEE},
isbn = {978-1-6654-3274-0},
}