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English(EN) EGRNet: A Lightweight Semantic Segmentation Network with Edge-Gated Refinement and Adversarial Sensing

EGRNet：具有边缘细化功能的轻量级语义分割网络

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了EGRNet，这是一种用于城市环境中实时语义分割的轻量级深度学习模型。该网络利用深度可分离卷积和膨胀残差块来有效捕获多尺度上下文信息。新颖的边缘门控细化模块增强了边界保持能力，而Squeeze-and-Excitation注意力机制则改善了特征表示。EGRNet仅拥有0.46百万个参数，在Cityscapes数据集上实现了65.28%的mIoU，并包含一个轻量级的对抗攻击检测策略以提高鲁棒性。 AI

影响 为自动驾驶系统和智慧城市的实时场景理解提供了更高效、更鲁棒的解决方案。

排序理由 发布了一篇详细介绍新型语义分割深度学习网络的新学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

EGRNet：具有边缘细化功能的轻量级语义分割网络

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发布了一篇详细介绍新型语义分割深度学习网络的新学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Bareera Qaseem, Mohsin Kamal, Muhammad Naveed Aman ·

    EGRNet：一种具有边缘门控细化和对抗感知功能的轻量级语义分割网络

    arXiv:2607.19617v1 Announce Type: new Abstract: As autonomous systems and smart cities continue to evolve, the demand for efficient and robust scene understanding becomes increasingly critical. Semantic segmentation plays a key role in enabling autonomous vehicles to comprehend c…

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