Flexible Variable-Rate Image Feature Compression for Edge-Cloud Systems
Author:
Affiliation:
1. Elmore Family School of Electrical and Computer Engineering, Purdue University,West Lafayette,IN,USA,47906
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10221939/10221894/10222898.pdf?arnumber=10222898
Reference27 articles.
1. A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing
2. Supervised Compression for Resource-Constrained Edge Computing Systems
3. Lightweight Compression of Intermediate Neural Network Features for Collaborative Intelligence
4. Variable Rate Deep Image Compression With a Conditional Autoencoder
5. Lightweight Compression Of Neural Network Feature Tensors For Collaborative Intelligence
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1. Balancing the Encoder and Decoder Complexity in Image Compression for Classification;2024-04-22
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