Stroke-based Character Recognition with Deep Reinforcement Learning

The stroke sequence of characters is significant for the character recognition task. In this paper, we propose a stroke-based character recognition (SCR) method. We train a stroke inference module under deep reinforcement learning (DRL) framework. This module extracts the sequence of strokes from characters, which can be integrated with character recognizers to improve their robustness to noise. Our experiments show that the module can handle complicated noise and reconstruct the characters. Meanwhile, it can also help achieve great ability in defending adversarial attacks of character recognizers.