A two-pass deep learning system for monitoring visual attributes of food in real-time during fluidized bed drying

HIGHLIGHTS

• What: Although one of the major aims of drying is to extend the shelf life of food, ironically, moisture content is not the food property that attracts consumers to the dried product. The first column is the 11 original image captured during the experiment; the second column are manually generated ground truth that was used to calculate how well the classical pipeline performed. When the authors compare the ground truth in Fig 6 to the segmented result from the CV pipeline, the authors would observe that the classical CV approach did not detect so many infocus peas . . .
  

   

  

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