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Updated: Jul 20, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
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Published on: February 6, 2020

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LPO-YOLOv5s:一个轻量级的倒机器人物体检测算法

Kanghui Zhao1, Biaoxiong Xie1, Xingang Miao1,2

  • 1Beijing Engineering Research Center of Monitoring for Construction Safety, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.

Sensors (Basel, Switzerland)
|July 29, 2023
PubMed
概括

这项研究介绍了LPO-YOLOv5s,这是一种轻量级的深度学习模型,用于检测造机器人中的倒孔. 它大大降低了模型尺寸和计算成本,同时保持了高精度,使其能够部署在资源有限的机器人上.

关键词:
在DSIFM中,您可以使用DSIFM这是YOLOv5s.造过程中的造过程.对象检测检测对象检测对象检测

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