We presented a machine learning-based method to recognize suspension by distinguishing dispersoid-dependent speckle patterns using a convolutional neural network. The dispersoid size and concentration-related transmissive speckle patterns were recorded by a lensless camera when a coherent He-Ne laser irradiated the suspension. Firstly we realized the recognition of the polystyrene microspheres-dispersed suspensions with different particle sizes and the recognition of several common suspensions including protein powder and milk powder with similar concentration. Further recognition from three different food suspensions with unknown concentration was achieved with high accuracy of 99%. The experimental results confirm that this non-contact method could find applications in the measurement and classification of suspension liquid containing micrometers-sized particles.

中文翻译：

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基于斑点学习的基于斑点图案的悬浮液识别

我们提出了一种基于机器学习的方法，该方法通过使用卷积神经网络来区分弥散性散斑图样来识别悬浮。当相干He-Ne激光照射悬浮液时，用无透镜相机记录了分散体的大小和与浓度有关的透射斑图。首先，我们认识到了不同粒径的聚苯乙烯微球分散悬浮液的识别，以及几种常见悬浮液的识别，包括浓度相似的蛋白质粉和奶粉。三种未知浓度不同的食品悬浮液的进一步识别达到了99％的高精度。