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A Neural Network-based Interframe Prediction for HEVC

A Neural Network-based Interframe Prediction for HEVC
	© 2022 by IJETT Journal
	Volume-70 Issue-1
	Year of Publication : 2022
	Authors : Kanike Sreenivasulu, T V K Hanumantha Rao
	DOI :  10.14445/22315381/IJETT-V70I1P223

How to Cite?

Kanike Sreenivasulu, T V K Hanumantha Rao, "A Neural Network-based Interframe Prediction for HEVC," International Journal of Engineering Trends and Technology, vol. 70, no. 3, pp. 201-211, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I1P223

Abstract
Exploration of spatial and temporal redundancies in video data is one of the most important processes in video encoding procedures, contributing to the high compression capability of the H.265 architecture, one of the latest video codecs. The aim of this paper is to come up with a deep learning-based approach for the same and contrast it with the accuracy current motion vector-based prediction system.

Keywords
HEVC, H.265, inter-frame, neural networks, Video Compression, LSTMs.

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