The identification and imaging of pollen grains in-flight was performed via illumination of the pollen grains with three collinear laser beams that had central wavelengths of 450 nm, 520 nm and 635 nm. Two neural networks are reported here; the first neural network was able to categorise pollen grain species from their scattering patterns with∼86% accuracy, while the second neural network generated images of the pollen grains from their scattering patterns. This work demonstrates the potential application of laser scattering and deep learning for real-world in-flight pollen identification.

中文翻译：

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通过激光散射和深度学习对花粉粒进行飞行传感

飞行中花粉粒的识别和成像是通过用中心波长为 450 nm、520 nm 和 635 nm 的三束共线激光束照射花粉粒来进行的。这里报告了两个神经网络；第一个神经网络能够根据其散射模式对花粉粒种类进行分类，准确率约为 86%，而第二个神经网络则根据其散射模式生成花粉粒的图像。这项工作展示了激光散射和深度学习在现实世界中飞行花粉识别中的潜在应用。