Abstract: Traditional recommendation systems primarily rely on collaborative filtering, which struggles to effectively capture the dynamic changes in user interests. Sequential recommendation ...

Harvard's free programming classes teach you how to think, debug, and adapt in an AI-driven world where knowing code matters more than ever.

Abstract: To better protect and restore ancient mural art, this study proposes an improved adaptive sample block Criminisi algorithm to address the shortcomings of traditional manual restoration ...