Reinforcement Learning for Rate-Distortion Optimized Hierarchical Prediction Structure-Reference-Cited by-同舟云学术

Reinforcement Learning for Rate-Distortion Optimized Hierarchical Prediction Structure

Published:2023 Issue: Volume:11 Page:20240-20253
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Lee Jung-Kyung¹,Kim Nayoung¹,Kang Je-Won¹^ORCID

Affiliation:

1. Department of Electronic and Electrical Engineering, Ewha Womans University, Seoul, South Korea

Funder

NRF through MSIT

Institute of Information and Communications Technology Planning and Evaluation

MSIT through the Information Technology Research Center

Korean Government, MSIT, “Development of ultra high resolution unstructured plenoptic video storage, compression, and streaming technology for medium to large space,”

supervised by IITP

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10054024.pdf?arnumber=10054024

Reference58 articles.

1. Lagrangian Multiplier Adaptation for Rate-Distortion Optimization With Inter-Frame Dependency

2. Very deep convolutional networks for large-scale image recognition;simonyan;arXiv 1409 1556,2014

3. Coding Order Decision of B Frames for Rate-Distortion Performance Improvement in Single-View Video and Multiview Video Coding

4. Adam: A method for stochastic optimization;kingma;arXiv 1412 6980,2014

5. Adaptive key-frame selection based on image features in Distributed Video Coding

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