3 accepted papers
While the deep learning-based image deraining methods have made great progress in recent years, there are two major shortcomings in their application in real-world situations. Firstly, the gap between the low-level vision task represented by rain removal and the high-level vision task represented by
AMR-to-text generation is a challenging task of generating texts from graph-based semantic representations. Recent studies formalize this task a graph-to-sequence learning problem and use various graph neural networks to model graph structure. In this paper, we propose a novel approach that generate…
This paper presents an observer-integrated Reinforcement Learning (RL) approach, called Disturbance OB-server Network (DOB-Net), for robots operating in environments where disturbances are unknown and time-varying, and may frequently exceed robot control capabilities. The DOB-Net integrates a distur…