Q-learning uses a table to store all state-action pairs. Q-learning is a model-free RL algorithm, so how could there be the one called Deep Q-learning as deep means using DNN; or maybe the state-action table (Q-table) is still there but the DNN is only for input reception (eg. images)?

Q-network seems not a term, and Deep Q-network seems an implementation of Deep Q-learning.

Q-learning, Deep Q-learning, and Deep Q-network, what are the differences? May be there a comparison table between these 3 terms?