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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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Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
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一个高质量的水下声学数据集用于算法开发和分析.

Victor Lobo1,2, Nuno Pessanha Santos3,4,5, Ricardo Moura1,6

  • 1Portuguese Navy Research Center (CINAV), Portuguese Naval Academy (Escola Naval), Almada, 2810-001, Portugal.

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概括
此摘要是机器生成的。

沃尔夫塞特声学数据集为算法开发提供了高质量的水声机录音. 这一优化的数据集简化了声学和声纳研究人员的数据再利用.

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科学领域:

  • 声学数据分析数据分析.
  • 水音箱技术的使用.
  • 信号处理 信号处理

背景情况:

  • 高质量的数据集对于开发和分析算法至关重要.
  • 数据采集可能是昂贵和耗时的,需要优化,以便重复使用.
  • 现有的声学数据集可能缺乏高级算法训练所需的保真度.

研究的目的:

  • 为了介绍Wolfset,一个新的声学数据集.
  • 为声学算法开发提供高质量,可重复使用的数据集.
  • 展示一种系统的方法来创建多样化和准确的声学数据集.

主要方法:

  • 在无声水箱中使用了Bruel & Kjaer的8104型水声机.
  • 从船外发动机和模型船的电机 (目标) 记录的声学数据.
  • 集成的外部瞬态和噪声来模拟现实世界的声学条件.

主要成果:

  • 创建了一个高保真度的无外部干扰的声学数据集.
  • 该数据集捕捉了各种声源和环境条件.
  • 证明了数据集适合用于算法开发和分析.

结论:

  • 沃尔夫塞特数据集为推进声学算法研究提供了宝贵的资源.
  • 它的系统结构确保了准确性和多样性,用于强大的算法训练.
  • 优化数据采集促进了更广泛的研究可访问性和应用.