The philosophy of our algorithm is gradual transfer of knowledge from the source to the target domain while being cognizant of similarity between two domains.
the proposed algorithm iteratively learns discriminative target specific features from such perplexing data and translates it to an improvement of at least 6.4% and 3.5% over the baseline and the SCL respec- Figure 7: Results comparing the accuracy of the proposed approach with existing techniques for cross domain categorization on the real world dataset.