Name
Abstract | ||
|---|---|---|
This paper analyses the deep image compression system that contains an encoder, quantizer, entropy model and decoder optimized by a joint rate-distortion framework. The current model implements a channel-level variable quantization network to dynamically allocate and withdraw the bitrates from significant and negligible channels. Its main specific is the usage of the variable quantization controll... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/EUROCON52738.2021.9535628 | IEEE EUROCON 2021 - 19th International Conference on Smart Technologies |
Keywords | DocType | ISBN |
Convolutional neural networks,Deep learning,Deep Image Compression,Channel-Level Variable Quantization,Deep Neural Networks | Conference | 978-1-6654-3299-3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dmytro Vasylenko | 1 | 0 | 0.34 |
| Sergii Stirenko | 2 | 53 | 14.13 |
| Yuri G. Gordienko | 3 | 50 | 8.93 |