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相关概念视频

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Internal Combustion Engine

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The internal combustion engine is a heat engine that uses the byproducts of combustion as the working fluid instead of using a heat transfer medium to transfer heat. The combustion is done in a way that produces high-pressure combustion products that can be expanded through a turbine or piston to create work. Internal combustion engines can again be categorized into three kinds: (1) spark ignition gasoline engines, most commonly used in automobiles, (2) compression ignition diesel engines that...
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Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
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The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
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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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In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
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基于深度学习的船舶发动机室火灾检测

Jinting Zhu1, Jundong Zhang1, Yongkang Wang1

  • 1College of Marine Engineering, Dalian Maritime University, Dalian 116026, China.

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

船舶发动机房火灾存在重大风险. 这项研究增强了YOLOv7微型深度学习,以更快,更准确地检测火灾,提高海上安全.

科学领域:

  • 海上安全的航行.
  • 人工智能的人工智能
  • 计算机视觉 计算机视觉

背景情况:

  • 船舶的火灾,特别是机房的火灾,由于偏远和复杂的环境,造成了严重的安全挑战.
  • 船舶机房的传统火灾检测方法在速度和准确性上是有限的.
  • 深度学习为快速和精确的火灾检测提供了一个有希望的方法.

研究的目的:

  • 为了增强YOLOv7微型模型,以改善船舶机房的火灾检测.
  • 提高船舶火灾检测系统的速度和准确性.
  • 解决海上环境中传统火灾检测方法的局限性.

主要方法:

  • 改进了YOLOv7微型模型,包括部分卷积 (PConv) 和协调注意力 (CA) 机制.
  • 利用SIoU作为损失函数来加速模型的融合并提高准确性.
  • 开发并使用船舶机房火灾的定制数据集进行培训和评估.

主要成果:

  • 改进的YOLOv7微型模型在mAP@0.5.5中实现了2.6%的增长.
  • 检测速度提高了每秒10 (fps).
  • 这些修改成功地提高了特征提取和检测性能.
关键词:
这就是SIOUU的意思.这是一个YOLOv7-tiny.协调注意力机制 协调注意力机制深度学习是一种深度学习.火灾检测系统的火灾检测系统.部分卷积的部分卷积

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结论:

  • 改进的YOLOv7微型模型有效地满足了船舶机房快速准确火灾检测的要求.
  • 集成PConv,CA和SIoU显著提高了基于深度学习的火灾检测系统的性能.
  • 这一进步有助于提高海上安全,因为它可以更快地应对机房火灾.