Link: http://drug.mfds.go.kr/html/index.jsp#

  Image Crop/Resizing ( Final Image Size: 1024 × 512 × 3 )

  Label Naming

  Model: Baisc ResNet18
  
  Augmentation: Vertical Flip / Tilt / Scaling / Shear / Elastic Distortion

  1. Shape (11 Types)
  Validation Acc: 91.87%

  2. Front Color (16 Types)
  Validation Acc: 90.23%

  3. Back Color (16 Types)
  Validation Acc: 91.08%

  ________________________________________________________________________________________________________________


  Total Acc: 75.50%       
  (Each model was trained with 50 epochs)

  1. Shape (11 Types) 
  Validation Acc: 91.55% 

  2. Front Color (16 Types) 
  Validation Acc: 91.70% 

  3. Back Color (16 Types)
  Validation Acc: 90.97%
  
  ________________________________________________________________________________________________________________
  
  Total Acc: 76.37% 
  (Model was trained with 150 epochs)
  
  Loss Weight
  Shape : Front Color : Back Color = 1 : 1 : 1

  1. Shape
  
  Model: Resnet18
  
  Drop-out rate: 0.1
  
  Aleatoric Uncertainty: 0.0085
  
  Epistemic Uncertainty: 0.0001

  Validation Acc: 86.63% (8 epoch Train)
  
  ________________________________________________________________________________________________________________

  2. Front Color
  
  Model: Resnet18
  
  Drop-out rate: 0.1
  
  Aleatoric Uncertainty: -
  
  Epistemic Uncertainty: -

  Validation Acc: -
  
  ________________________________________________________________________________________________________________
        
  3. Back Color
  
  Model: Resnet18
  
  Drop-out rate: 0.1
  
  Aleatoric Uncertainty: -
  
  Epistemic Uncertainty: -

  Validation Acc: -
  
  ________________________________________________________________________________________________________________
  
  Total Acc: -

  1. All (Shape + Front Color + Back Color)
  
  Model: Resnet18
  
  Drop-out rate: 0.1
 
  Aleatoric Uncertainty: -
  
  Epistemic Uncertainty: -

  Validation Shape Acc: 88.09%
  
  Validation Color1 Acc: 84.08%
  
  Validation Color2 Acc: 85.16%
  
  ________________________________________________________________________________________________________________
  
  Total Acc: 63.32%    
  
  Loss Weight
  Shape : Front Color : Back Color = 1 : 1 : 1

  Reference Paper: 
  
  1. Real-world Pill Segmentation based on Superpixel Merge using Region Adjacency Graph
     (Link: http://www.scitepress.org/Papers/2017/61358/61358.pdf)