how to improve the performance of the CNN model (Machine Learning - Deep Learning)

Question

I am trying to train a model based on CNN,

Training data is the image of lunar lander, but the performance of model is not good, the accuracy is about 45%, I try to add more layer to improve it, but it still doesn't work well, could any one provide some ideas about how to improve it. Label: up down left right (0,1,2,3) Sample rate: 0.1

The Training data has converted from image to data Label:

here is some of my code:

model = Sequential()

model.add(Conv2D(32, (3, 3), padding='same', input_shape=(CHANNELS, ROWS, COLS), activation='relu'))
model.add(Conv2D(32, (3, 3), padding='same', activation='relu'))
model.add(Conv2D(32, (3, 3), padding='same', activation='relu'))
model.add(Conv2D(32, (3, 3), padding='same', activation='relu'))
model.add(Conv2D(32, (3, 3), padding='same', activation='relu'))

model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Flatten())

model.add(Dense(128, activation='relu'))
model.add(Dropout(0.5))

model.add(Dense(num_classes, activation = 'softmax'))
.summary()

Answer 1

I would experiment a lower dropout rate. Dropouts are used to prevent overfitting. It looks like your model isn't even fitting in the first place.