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...
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Main Authors: | , , , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/165565 |
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Institution: | Nanyang Technological University |
Language: | English |