Visual domain adaptation via transfer feature learning

@article{Tahmoresnezhad2016VisualDA,
  title={Visual domain adaptation via transfer feature learning},
  author={Jafar Tahmoresnezhad and Sattar Hashemi},
  journal={Knowledge and Information Systems},
  year={2016},
  volume={50},
  pages={585-605}
}
One of the serious challenges in computer vision and image classification is learning an accurate classifier for a new unlabeled image dataset, considering that there is no available labeled training data. Transfer learning and domain adaptation are two outstanding solutions that tackle this challenge by employing available datasets, even with significant difference in distribution and properties, and transfer the knowledge from a related domain to the target domain. The main difference between… CONTINUE READING