Electronic apparatus and controlling method thereof

A method of controlling an electronic apparatus, the method comprising:

• identifying a type of an input image by inputting the input image to a second artificial intelligence model trained to identify a type of an image by predicting an image processing result by each of a plurality of first artificial intelligence models trained to perform image processing differently from each other;
• processing the input image by inputting the input image to one of the plurality of first artificial intelligence models based on the identified type;
• and
• obtaining a weighted value regarding a plurality of types related to the input image by inputting the input image to the second artificial intelligence model.

A computer-implemented method of training a neural network for image processing comprising:

• collecting a set of digital sample images from a database;
• inputting the collected set of digital sample images into a plurality of first neural network models, so as to obtain a plurality of outputs, wherein the plurality of first neural network models are trained to perform image processing differently from each other;
• training, in a second neural network model, relationships between the set of digital sample images and a side effect type corresponding to each digital sample image using the obtained plurality of outputs, wherein the side effect type corresponds to a side effect of processing by a respective one of the plurality of first neural network models;
• identifying a side effect type of an input digital image by inputting the input digital image to the second neural network model;
• and processing the input digital image by inputting the input digital image to one of the plurality of first neural network models that corresponds to the identified defect type.