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相关概念视频

Color Vision01:24

Color Vision

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Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
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Qualitative Identification of Carboxylic Acids, Boronic Acids, and Amines Using Cruciform Fluorophores
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ColorNet:基于人工智能的框架,用于使用色度传感器阵列检测猪肉的新鲜度.

Guangzhi Wang1, Yuchen Guo1, Yang Yu2

  • 1School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China; Institute of advanced sensor technology, Northeast Electric Power University, Jilin 132012, China.

Food chemistry
|January 10, 2025
PubMed
概括
此摘要是机器生成的。

一个新的色度传感器阵列 (CSA) 和ColorNet框架准确地检测猪肉的新鲜度. 这项技术为实时质量监测提供了具有成本效益的解决方案,确保食品安全和消费者健康.

关键词:
颜值测量传感器阵列为一个颜色测量阵列.梯度激活映射映射 梯度激活映射神经网络的神经网络的神经网络猪肉新鲜度检测器 猪肉新鲜度检测器

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Colorimetric Paper-based Detection of Escherichia coli, Salmonella spp., and Listeria monocytogenes from Large Volumes of Agricultural Water
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科学领域:

  • 食品科学 食品科学 食品科学
  • 分析化学 分析化学
  • 传感器技术 传感器技术

背景情况:

  • 猪肉的新鲜度对消费者健康,口味和营养至关重要.
  • 目前用于猪肉新鲜度检测的色度传感器阵列 (CSA) 系统存在高成本,低准确性和平台限制.

研究的目的:

  • 开发一个高效准确的CSA和深度学习框架 (ColorNet) 来检测猪肉的新鲜度.
  • 创建一个具有成本效益和可靠的实时猪肉质量评估方法.

主要方法:

  • 使用pH和化物/子指标设计了一个53点的CSA.
  • 欧几里德距离方法优化了传感器到24个关键阵列点.
  • 使用深度学习模型ColorNet来分析颜色变化以检测新鲜度.

主要成果:

  • ColorNet框架在实时检测猪肉新鲜度方面实现了99.5%的准确性.
  • 一个简化的12点CSA,使用梯度激活映射进行了优化,在实际应用中保持了99%的准确性.

结论:

  • 开发的CSA和ColorNet框架为监测猪肉新鲜度提供了高度准确和高效的解决方案.
  • 这项技术为提高食品安全,质量控制和消费者对猪肉行业的信心提供了巨大的潜力.