English(EN) Input Resolution Matters: Real-Time Object Detection Latency

新模型将输入分辨率与目标检测延迟联系起来

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-14 04:00

研究人员开发了一个新模型，用于理解输入分辨率如何影响实时目标检测系统的延迟。该模型将总延迟视为预处理、推理和后处理阶段的卷积，其参数取决于源图像分辨率。使用 YOLOv11n 在 NVIDIA Jetson Orin NX 上对 COCO2017 图像进行的实验表明，这种分辨率感知参数化可以改善分布近似，尤其是在使用 Normal 和 Gamma 等更灵活的模型时。 AI

影响通过考虑输入分辨率对延迟的影响，为优化实时目标检测系统提供了一个框架。

排序理由学术论文，详细介绍了目标检测延迟的新模型。[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 →

本文如何被排名

Signal score: 24 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 学术论文，详细介绍了目标检测延迟的新模型。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, infra; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Qingyang Zhang, Fumio Machida, Laura Carnevali · 2026-09-14 04:00

输入分辨率很重要：实时物体检测延迟

arXiv:2609.12920v1 Announce Type: new Abstract: We model total latency as the convolution of preprocessing, inference, and postprocessing distributions under a simplifying independence approximation, with selected stage parameters expressed as functions of source-image resolution…

本文如何被排名

报道来源 [1]

输入分辨率很重要：实时物体检测延迟

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