Recognition of Suspension Liquid Based on Speckle Patterns Using Deep Learning

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Abstract
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.
Funding Information
  • Zhejiang Provincial Natural Science Foundation of China (LY15F050011, LY21F050005)

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