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相关概念视频

Survey Safety01:28

Survey Safety

368
Surveying near highways, rough terrain, or power lines involves significant risks. Working along highways is particularly dangerous and requires the use of warning signs and flagmen. It is safest to avoid working directly on roads and use offsets whenever possible. When highway work is unavoidable, it must follow all safety guidelines. Surveyors should wear bright clothing, such as orange reflective vests, to ensure visibility to motorists, coworkers, and hunters. In construction zones, wearing...
368
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Topographic Surveying and Contours01:29

Topographic Surveying and Contours

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Topographic surveying is critical for documenting the Earth's surface, focusing on capturing elevations, slopes, and natural and man-made features. It is essential in construction planning, water resource management, and land-use analysis. The primary outcome of such surveys is a topographic map, which uses contour lines to visually represent the shape and slope of the terrain, providing valuable insights into the landscape's characteristics.Contour lines are fundamental to understanding the...
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Detection of Black Holes01:10

Detection of Black Holes

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Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
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相关实验视频

Updated: Jan 13, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.0K

增强的实时高速公路对象检测用于施工区安全使用YOLOv8s-MTAM.

Wen-Piao Lin1,2, Chun-Chieh Wang1, En-Cheng Li1

  • 1Department of Electrical Engineering, Chang Gung University, Taoyuan 33303, Taiwan.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
概括

这项研究通过使用改进的YOLOv8s系统与运动时间注意模块 (MTAM) 来增强自动驾驶对象检测. 该系统在动态高速公路建设区识别危险时达到高精度.

关键词:
这就是YOLOv8的意义.自动驾驶自动驾驶的自动驾驶.建筑车辆 建筑车辆数据增强数据增强运动时间的注意力.对象检测检测对象检测对象检测警告标志警告标志警告标志

相关实验视频

Last Updated: Jan 13, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.0K

科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 对象检测对于自动驾驶安全至关重要,特别是在动态高速公路建设区.
  • 现有的系统与这些环境中常见的高速,封闭或模糊对象作斗争.

研究的目的:

  • 开发一个增强的YOLOv8s物体检测系统,以提高在施工区自动驾驶的稳定性.
  • 整合一个运动时态注意模块 (MTAM) 来更好地检测动态和封闭的物体.

主要方法:

  • 一个增强的YOLOv8s架构,包括一个CSP骨干,FPN-PAN功能融合,以及先进的损失功能.
  • 整合了一种新型的运动时间注意力模块 (MTAM),利用时间卷曲和注意力机制.
  • 在一个由34,240张图像组成的定制数据集上进行培训,这些图像具有广泛的数据增强和9-Mosaic转换.

主要成果:

  • 实现了高性能指标:mAP ((IoU[0.5]) 的90.77 ± 0.68%和mAP ((IoU[0.5:0.95]) 的70.20 ± 0.33%.
  • 证明了强大的现实世界识别率:建筑车辆96%;警告标志92%;旗84%.
  • MTAM有效地提高了对模糊和部分遮蔽物体的检测.

结论:

  • 增强的YOLOv8s系统与MTAM显著提高了对象检测可靠性,在具有挑战性的高速公路建设区.
  • 该框架显示了智能交通系统实时部署的巨大潜力,以提高安全性.