English(EN) Input-Adaptive Gating of a Dehazing Front-End for On-Device Perception in Smoke-Obscured Environments

AI系统自适应去雾，提升烟雾中视觉清晰度

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-01 04:00

研究人员开发了一种用于烟雾遮挡环境中设备端感知的输入自适应去雾前端系统。该系统在搭载TensorFlow Lite的Raspberry Pi 4 Model B上进行了测试，旨在通过增强烟雾条件下的边缘检测来改进消防员辅助。自适应门控方法仅在雾度估计超过特定阈值时选择性地应用去雾过程，与始终去雾或从不进行去雾相比，提高了准确性并显著减少了处理时间。 AI

影响优化了在挑战性环境中的设备端AI感知能力，可能改善关键应用中的实时分析。

排序理由学术论文，详细介绍了针对特定环境挑战的计算机视觉新方法。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Seongjun Kang, Ishaan Garg, Vishnu Bharadwaj · 2026-09-01 04:00

用于烟雾遮挡环境中设备端感知的输入自适应门控去雾前端

arXiv:2608.30034v1 Announce Type: new Abstract: Two-stage vision pipelines often place an enhancement network before a task network, on the assumption that a cleaner input produces a better output. We evaluate this in a firefighter assistance pipeline, where a dehazer precedes an…

本文如何被排名

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用于烟雾遮挡环境中设备端感知的输入自适应门控去雾前端

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