arXiv Open Access 2022

Efficient Feature Compression for Edge-Cloud Systems

Zhihao Duan Fengqing Zhu
Lihat Sumber

Abstrak

Optimizing computation in an edge-cloud system is an important yet challenging problem. In this paper, we consider a three-way trade-off between bit rate, classification accuracy, and encoding complexity in an edge-cloud image classification system. Our method includes a new training strategy and an efficient encoder architecture to improve the rate-accuracy performance. Our design can also be easily scaled according to different computation resources on the edge device, taking a step towards achieving a rate-accuracy-complexity (RAC) trade-off. Under various settings, our feature coding system consistently outperforms previous methods in terms of the RAC performance.

Topik & Kata Kunci

Penulis (2)

Z

Zhihao Duan

F

Fengqing Zhu

Format Sitasi

Duan, Z., Zhu, F. (2022). Efficient Feature Compression for Edge-Cloud Systems. https://arxiv.org/abs/2211.09897

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2022
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓