Design and Application of Model Compression and Management Platform

DOI

10.2991/978-94-6463-262-0_64How to use a DOI?

Keywords

Software design; Model compression; Neural network

Abstract

In order to facilitate the deployment of neural network models on edge devices and improve the computational speed of the models, compressing the volume of neural network models has become a key problem. However, currently neural network compression can only be achieved through programming, which is not only inefficient but also inconvenient for model management. Therefore, we design and develop a model compression and management platform that integrates existing model pruning and quantization technologies, while incorporating model management and dataset management functions. It not only facilitates the management of datasets and models, but also meets needs for fast model pruning and quantization.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Hao Li
AU  - Chuangbo Hao
PY  - 2023
DA  - 2023/10/09
TI  - Design and Application of Model Compression and Management Platform
BT  - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)
PB  - Atlantis Press
SP  - 618
EP  - 627
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-262-0_64
DO  - 10.2991/978-94-6463-262-0_64
ID  - Li2023
ER  -