April 25, 2024, 7:46 p.m. | Parham Zilouchian Moghaddam, Mehdi Modarressi, Mohammad Amin Sadeghi

cs.CV updates on arXiv.org arxiv.org

arXiv:2401.01163v2 Announce Type: replace
Abstract: Video content has experienced a surge in popularity, asserting its dominance over internet traffic and Internet of Things (IoT) networks. Video compression has long been regarded as the primary means of efficiently managing the substantial multimedia traffic generated by video-capturing devices. Nevertheless, video compression algorithms entail significant computational demands in order to achieve substantial compression ratios. This complexity presents a formidable challenge when implementing efficient video coding standards in resource-constrained embedded systems, such as IoT …

abstract arxiv class compression cs.cv cs.mm deep learning devices generated internet internet of things iot multimedia networks novel quality traffic type video video compression video quality video quality enhancement

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US