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相关概念视频

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

646
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
646
Downsampling01:20

Downsampling

155
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
155
Reducing Line Loss01:18

Reducing Line Loss

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In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
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基于点云压缩的时间聚合的神经形态视觉传感器数据的无损编码.

Jayasingam Adhuran1, Nabeel Khan2, Maria G Martini1

  • 1Faculty of Engineering, Computing, and the Environment, Kingston University London, Penrhyn Rd., Kingston upon Thames KT1 2EE, UK.

Sensors (Basel, Switzerland)
|March 13, 2024
PubMed
概括

一种新的方法,基于点云压缩 (TALEN-PCC) 的事件的时间聚合无损编码,增强了神经形态视觉传感器 (NVS) 的数据压缩. 这种方法提供了更好的压缩比率,特别是对于更简单的场景和更长的时间间隔.

关键词:
神经形态的尖峰事件.神经形象视觉传感器 (NVS)点云压缩点云压缩网膜是一种网膜.这是一个spike编码.

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科学领域:

  • 计算机视觉 计算机视觉
  • 数据压缩数据压缩
  • 传感器技术 传感器技术

背景情况:

  • 神经形态视觉传感器 (NVS) 与传统相机相比,提供了低功耗和高动态范围等优势.
  • 虽然NVS数据本身的数据速率较低,但可以进一步压缩以实现高效的存储和传输.
  • 已经探索了以前的方法,例如基于时间聚合的无损视频编码用于神经形象视觉传感器数据 (TALVEN).

研究的目的:

  • 为NVS数据引入和评估一种新的压缩策略.
  • 将新策略的有效性与以前的方法进行比较.
  • 分析场景复杂度和时间聚合间隔对压缩性能的影响.

主要方法:

  • 利用NVS事件的时间聚合.
  • 使用点云压缩技术编码时间聚合数据.
  • 实施基于点云压缩 (TALEN-PCC) 策略的事件的时间聚合无损编码.

主要成果:

  • 与TALVEN战略相比,TALEN-PCC在测试的数据集上显示出更高的压缩比率.
  • 压缩收益在低事件率和低复杂度场景中最为显著.
  • 超过5ms的时间聚合间隔可以实现更高的压缩,尽管在5ms以下的间隔中,与最先进的技术相比,收益会减少.

结论:

  • 在NVS数据的无损压缩方面,TALEN-PCC是有效的进步.
  • 该方法的性能对场景特征和时间聚合设置敏感.
  • 进一步的研究可能会为各种NVS应用和数据类型优化TALEN-PCC.