CNN with Multi channel input or CNN with Multi instance learning?
One of the other approach you can try is multi input &amp; single output approach in which passing these 2 images to 2 different layer from there different layer then concatenation of the layers to perform classification task.

It can be done using keras Functional API

input1 = keras.layers.Input(shape=(1,))
input2 = keras.layers.Input(shape=(1,))

cnn1   = keras.layers.Conv2D(32, 3, activation=keras.activation.relu)(input1)
cnn2   = keras.layers.Conv2D(32, 3, activation=keras.activation.relu)(input2)

merged = keras.layers.Concatenate(axis=1)([input1, input2])

dense1 = keras.layers.Dense(2, activation=keras.activations.relu)(merged)
output = keras.layers.Dense(1, activation=keras.activations.sigmoid)(dense1)
model10 = keras.models.Model(inputs=[input1, input2], output=output)


When passing data to model create separate arrays of input those 2 images set.

model0.fit([array_1, array_2],output, batch_size=16, epochs=100)