Senlin Fang

According to our database, Senlin Fang authored at least 8 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Dynamic liquid volume estimation using optical tactile sensors and spiking neural network.

Binhua Huang, Senlin Fang, Meng Yin, Zhengkun Yi, Chaoxiang Ye, Xiaoyu Li, Zhenning Zhou, Xinyu Wu

Intell. Serv. Robotics, March, 2024

2023

TactONet: Tactile Ordinal Network Based on Unimodal Probability for Object Hardness Classification.

Senlin Fang, Zhengkun Yi, Tingting Mi, Zhenning Zhou, Chaoxiang Ye, Wanfeng Shang, Tiantian Xu, Xinyu Wu

IEEE Trans Autom. Sci. Eng., October, 2023

A Deep Learning Method Based on Triplet Network Using Self-Attention for Tactile Grasp Outcomes Prediction.

Chengliang Liu, Zhengkun Yi, Binhua Huang, Zhenning Zhou, Senlin Fang, Xiaoyu Li, Yupo Zhang, Xinyu Wu

IEEE Trans. Instrum. Meas., 2023

Evaluation of Continual Learning Methods for Object Hardness Recognition.

Yiwen Liu, Senlin Fang, Chengliang Liu, Jingnan Wang, Ke Mai, Yupo Zhang, Zhengkun Yi, Xinyu Wu

Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2023

2022

Depth Recognition of Hard Inclusions in Tissue Phantoms for Robotic Palpation.

Zhenning Zhou, Senlin Fang, Chaoxiang Ye, Tingting Mi, Binhua Huang, Xiaoyu Li, Zhengkun Yi, Xinyu Wu

Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2022

2021

Tactile Grasp Stability Classification Based on Graph Convolutional Networks.

Tingting Mi, Dashun Que, Senlin Fang, Zhenning Zhou, Chaoxiang Ye, Chengliang Liu, Zhengkun Yi, Xinyu Wu

Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2021

TactCapsNet: Tactile Capsule Network for Object Hardness Recognition.

Senlin Fang, Tingting Mi, Zhenning Zhou, Chaoxiang Ye, Chengliang Liu, Hancheng Wu, Zhengkun Yi, Xinyu Wu

Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2021

2020

Multimodal Surface Material Classification Based on Ensemble Learning with Optimized Features.

Xiang Liu, Hancheng Wu, Senlin Fang, Zhengkun Yi, Xinyu Wu

Proceedings of the 22nd IEEE International Conference on E-health Networking, 2020