English(EN) A lightweight convolutional neural network for target detection in an edge environment

为实时边缘设备目标检测开发轻量级CNN

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-09 05:00

研究人员开发了一种新的、轻量级的卷积神经网络（CNN），专门用于部署在边缘设备上。该CNN专为实时目标检测和分类而设计，在标准热传感器下，推理速度可达每秒20帧，检测范围超过400米。其设计优先考虑准确性、灵敏度和低误报率，使其适用于监控、安全和物体识别等应用。 AI

影响这种轻量级CNN可以实现资源受限的边缘设备上更复杂、实时的威胁检测和物体识别。

排序理由该集群包含一篇详细介绍新模型架构的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Hughes Perreault, Ola Ahmad, Daniel Czuboka · 2026-11-09 05:00

面向边缘环境目标检测的轻量级卷积神经网络

arXiv:2611.09756v1 Announce Type: new Abstract: This paper proposes a novel, lightweight convolutional neural network (CNN) designed for edge device deployment. The CNN is developed to recognize and classify threats or targets of interest. The model is equipped with a real-time h…