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Fabrication of Flexible Image Sensor Based on Lateral NIPIN Phototransistors
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柔性水凝传感器的最新进展:增强数据处理和机器学习,以实现智能感知.

Derrick Boateng1, Xukai Li2, Yuhan Zhu2

  • 1College of Applied Sciences, Shenzhen University, Shenzhen, 518060, China; Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, 518060, China; College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, 518188, China.

Biosensors & bioelectronics
|June 19, 2024
PubMed
概括

这篇评论探讨了机器学习 (ML) 如何增强灵活的水凝传感器,以实现智能感知. 它详细介绍了数据处理技术,这些技术对于推进可穿戴电子产品和软机器人的发展至关重要.

关键词:
数据处理数据处理.灵活的水凝传感器智能感知是一种智能感知.机器学习 (ML) 是指机器学习.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 电子工程 电子工程
  • 人工智能的人工智能

背景情况:

  • 基于水凝的柔性传感器对于可穿戴电子产品和软机器人至关重要.
  • 机器学习 (ML) 算法越来越多地被整合起来,以改善传感器数据处理.
  • 在专注于用于水凝传感器的ML驱动数据分析的审查中存在差距.

研究的目的:

  • 在柔性水凝传感中全面审查ML应用.
  • 检查用于原始传感器数据的数据处理技术.
  • 为这个领域的未来数据驱动应用提供洞察力.

主要方法:

  • 关于ML和水凝传感器近期进展的文献综述.
  • 对柔性水凝传感器数据的数据处理策略的分析.
  • 综合各种应用领域的发现.

主要成果:

  • ML算法显著提高了水凝传感器中的智能感知.
  • 为了提取有意义的信息,各种数据处理技术至关重要.
  • ML与水凝传感器的融合显示了先进应用的前景.

结论:

  • 机器学习集成是释放柔性水凝传感器全部潜力的关键.
  • 了解数据处理对于未来的创新至关重要.
  • 本综述为智能传感中的数据驱动的进步提供了路线图.