COMPUTER SYSTEM FOR MULTI-DOMAIN ADAPTIVE TRAINING BASED ON SINGLE NEURAL NETWORK WITHOUT OVERFITTING, AND METHOD THEREOF

摘要

Various embodiments relate to a computer system for multi-domain adaptive training based on a single neural network without overfitting, and a method thereof, and may be configured to normalize data sets of multiple domains, extract shared information that is shared between the normalized data sets, perform training on the basis of the extracted shared information to implement a training model, and transplant the training model to a target domain.