#Conv Layer 1
    model.add(Conv2D(64, kernel_size=3, activation='relu', input_shape=(75, 75, 3)))
    model.add(MaxPooling2D(pool_size=3, strides=2))
    #model.add(Dropout(0.2))

    #Conv Layer 2
    model.add(Conv2D(128, kernel_size=3, activation='relu', input_shape=(75, 75, 3)))
    model.add(MaxPooling2D(pool_size=3, strides=2))
    #model.add(Dropout(0.2))

    #Conv Layer 3
    model.add(Conv2D(256, kernel_size=3, activation='relu', input_shape=(75, 75, 3)))
    model.add(MaxPooling2D(pool_size=3, strides=2))
    #model.add(Dropout(0.2))

    #Conv Layer 4
    model.add(Conv2D(64, kernel_size=3, activation='relu', input_shape=(75, 75, 3)))
    model.add(MaxPooling2D(pool_size=3, strides=2))
    #model.add(Dropout(0.2))

    # Flatten
    model.add(Flatten())

    # Dense Layer 1
    model.add(Dense(256, activation='relu'))
    #model.add(Dropout(0.2))

    # Dense Layer 2
    model.add(Dense(512, activation='relu'))
    #model.add(Dropout(0.2))

    #Sigmoid Layer
    model.add(Dense(1))
    model.add(Activation('sigmoid'))