Academic Background and Problem Statement In recent years, deep learning models (Deep Neural Networks, DNNs) have achieved remarkable success in computer vision tasks. However, the training of these models relies heavily on large amounts of annotated data. When models are applied to new, unlabeled target domains, their generalization ability often ...