[Retracted] Enhanced Watershed Segmentation Algorithm-Based Modified ResNet50 Model for Brain Tumor Detection

Algorithm 2

Algorithm for computation of model loss and accuracy using ResNet50.

1 import ResNet50

 #Load the model

2 ResNet50 = = > DLT {ResNet50(Ll)}; Ed (ResNet50)

 #Change the required according to concept

3 Ed{ResNet50 + L(Do + F + Do + D) + apply act.(sigmoid) + apply Adam optimizer}

 #Edit into model last layer (transfer learning concept (add 04 layers (dropout layer (Do), flatten layer (F), dropout layer (Do), dense layer(D)), activate the sigmoid function, apply adam optimizer with values))

4 Generate Mt SET (Ep = 150, S/ Ep = 50, S/V = 25)

 #Generate the model training [Mt] and set the model epochs, set per epochs (S), and set per validation (V)

5 Generate graphs of MAcc & MLoss

 #Plot the model accuracy (MAcc) and model loss (MLoss)

6 Confusion_mtx = confusion_mtx(prediction)

 #Find out the accuracy of the model