Thanh-Binh Nguyen

h-index42
2papers
5,479citations

2 Papers

2.4IVNov 9, 2021
GDCA: GAN-based single image super resolution with Dual discriminators and Channel Attention

Thanh Nguyen, Hieu Hoang, Chang D. Yoo

Single Image Super-Resolution (SISR) is a very active research field. This paper addresses SISR by using a GAN-based approach with dual discriminators and incorporating it with an attention mechanism. The experimental results show that GDCA can generate sharper and high pleasing images compare to other conventional methods.

14.2ROFeb 14, 2019
Manipulating Soft Tissues by Deep Reinforcement Learning for Autonomous Robotic Surgery

Ngoc Duy Nguyen, Thanh Nguyen, Saeid Nahavandi et al.

In robotic surgery, pattern cutting through a deformable material is a challenging research field. The cutting procedure requires a robot to concurrently manipulate a scissor and a gripper to cut through a predefined contour trajectory on the deformable sheet. The gripper ensures the cutting accuracy by nailing a point on the sheet and continuously tensioning the pinch point to different directions while the scissor is in action. The goal is to find a pinch point and a corresponding tensioning policy to minimize damage to the material and increase cutting accuracy measured by the symmetric difference between the predefined contour and the cut contour. Previous study considers finding one fixed pinch point during the course of cutting, which is inaccurate and unsafe when the contour trajectory is complex. In this paper, we examine the soft tissue cutting task by using multiple pinch points, which imitates human operations while cutting. This approach, however, does not require the use of a multi-gripper robot. We use a deep reinforcement learning algorithm to find an optimal tensioning policy of a pinch point. Simulation results show that the multi-point approach outperforms the state-of-the-art method in soft pattern cutting task with respect to both accuracy and reliability.