What is the architecture of my CNN called and what should I change to make a FCN-8
from keras.layers import BatchNormalization, Dropout def unk(IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS): inputs = Input((IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS)) # Contracting path conv1 = Conv2D(32, (3, 3), activation=’relu’, kernel_initializer=’he_normal’, padding=’same’)(inputs) conv1 = BatchNormalization()(conv1) conv1 = Conv2D(32, (3, 3), activation=’relu’, kernel_initializer=’he_normal’, padding=’same’)(conv1) conv1 = BatchNormalization()(conv1) pool1 = MaxPooling2D((2, 2))(conv1) conv2 = Conv2D(64, (3, 3), activation=’relu’, kernel_initializer=’he_normal’, padding=’same’)(pool1) conv2 = BatchNormalization()(conv2) conv2 […]