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GANs enhance image transmission for connected vehicles

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new generative adversarial network (GAN)-based semantic communication framework designed to improve image transmission efficiency and fidelity in the Internet of Vehicles (IoV). This framework prioritizes semantic information based on driving safety, allocating bits and designing loss functions accordingly. The system aims to reconstruct high-quality images from corrupted semantic labels, demonstrating superior performance on the Cityscapes dataset compared to existing methods, even under challenging channel conditions like additive white Gaussian noise and Rayleigh channels. AI

IMPACT This research could lead to more robust and efficient visual data transmission in autonomous driving systems.

RANK_REASON Academic paper detailing a novel technical approach. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GANs enhance image transmission for connected vehicles

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Academic paper detailing a novel technical approach. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Ruixing Ren, Shan Chen, Junhui Zhao, Xiaoke Sun ·

    GAN-Based Semantic Communication for Image Transmission in IoV

    arXiv:2608.27989v1 Announce Type: new Abstract: For cooperative perception in the internet of vehicles, this paper proposes a generative adversarial network-based semantic communication framework to address the efficiency and fidelity bottlenecks of traditional communication syst…

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