计算机科学
人工神经网络
人工智能
移动设备
全息术
微粒
气溶胶
计算机视觉
模式识别(心理学)
环境科学
气象学
化学
光学
操作系统
物理
有机化学
作者
Yi Luo,Yijie Zhang,Tairan Liu,Alan Yu,Yichen Wu,Aydogan Ozcan
摘要
We present a computational mobile imaging device that captures holograms of aerosols through a virtual impactor, a flow-based device designed to detect aerosols. A differential detection scheme localizes all the flowing particles in air, and their auto-focused holograms are used to classify them using a trained neural network without any labels/stains. To test this cost-effective mobile device, we aerosolized different types of pollen (Bermuda, Elm, Oak, Pine, Sycamore, and Wheat) and achieved a blind testing classification accuracy of 92.91%. This cost-effective mobile system can be used as a long-term air quality monitor to automatically count/sense particulate matter and various allergens.
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