METHOD AND APPARATUS FOR RECOGNIZING HANDWRITTEN CHARACTERS USING FEDERATED LEARNING

Provided is a method for recognizing handwritten characters in a terminal through federated learning. In the method, a first common prediction model for recognizing text from handwritten characters input from a user is applied, the handwritten characters are received from the user, feature values are extracted from an image including the handwritten characters, the feature values are input to the first common prediction mode, first text information is determined from an output of the first common prediction model, the first text information and a second text information received from the user for error correction of the first text information are cached, and the first common prediction model is learned using the image including the handwritten characters, the first text information, and the second text information. In this way, the terminal can determine the text from the handwritten characters input by the user, and can learn the first common prediction model through a feedback operation of the user.