Latency-constrained DNN architecture learning for edge systems using zerorized batch normalization
Deep learning applications have been widely adopted on edge devices, to mitigate the privacy and latency issues of accessing cloud servers. Deciding the number of neurons during the design of a deep neural network to maximize performance is not intuitive. Particularly, many application scenarios are...
Saved in:
Main Authors: | , , , , , , |
---|---|
其他作者: | |
格式: | Article |
語言: | English |
出版: |
2023
|
主題: | |
在線閱讀: | https://hdl.handle.net/10356/165565 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|