Robotic Grasping of Novel Objects from RGB-D Images by Using Multi-Level Convolutional Neural Networks. - Qunchao Yu; Weiwei Shang 001; Zengzhi Zhao; Shuang Cong; Yunjiang Lou (ICIA, 2018)

Learning Optimal Grasping Posture of Multi-Fingered Dexterous Hands for Unknown Objects. - Fangjing Song; Zengzhi Zhao; Wei Ge; Weiwei Shang 001; Shuang Cong (ROBIO, 2018)

Grasp prediction and evaluation of multi-fingered dexterous hands using deep learning. - Zengzhi Zhao; Weiwei Shang 001; Haoyuan He 002; Zhijun Li 001 (Robotics Auton. Syst., 2020)

Robotic Grasping of Unknown Objects Using Novel Multilevel Convolutional Neural Networks: From Parallel Gripper to Dexterous Hand. - Qunchao Yu; Weiwei Shang 001; Zengzhi Zhao; Shuang Cong; Zhijun Li 001 (IEEE Trans Autom. Sci. Eng., 2021)

Deep Learning Method for Grasping Novel Objects Using Dexterous Hands. - Weiwei Shang 001; Fangjing Song; Zengzhi Zhao; Hongbo Gao 001; Shuang Cong; Zhijun Li 001 (IEEE Trans. Cybern., 2022)