Senlin Fang

Orcid: 0000-0001-6005-6813

According to our database1, Senlin Fang authored at least 13 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Bibliography

2025
Evetac Meets Sparse Probabilistic Spiking Neural Network: Enhancing Snap-Fit Recognition Efficiency and Performance.
IEEE Robotics Autom. Lett., June, 2025

Semisupervised Domain Adaptation for Wafer Map Defect Recognition via Cross-Alignment Network.
IEEE Trans. Instrum. Meas., 2025

Multi-Branch Multi-Scale Channel Fusion Graph Convolutional Networks With Transfer Cost for Robotic Tactile Recognition Tasks.
IEEE Trans Autom. Sci. Eng., 2025

TactCLNet: Tactile Continual Learning Network Based on Generative Replay for Object Hardness Recognition.
IEEE Trans Autom. Sci. Eng., 2025

2024
Dynamic liquid volume estimation using optical tactile sensors and spiking neural network.
Intell. Serv. Robotics, March, 2024

Probabilistic Spiking Neural Network for Robotic Tactile Continual Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
TactONet: Tactile Ordinal Network Based on Unimodal Probability for Object Hardness Classification.
IEEE Trans Autom. Sci. Eng., October, 2023

A Deep Learning Method Based on Triplet Network Using Self-Attention for Tactile Grasp Outcomes Prediction.
IEEE Trans. Instrum. Meas., 2023

Evaluation of Continual Learning Methods for Object Hardness Recognition.
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.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2022

2021
Tactile Grasp Stability Classification Based on Graph Convolutional Networks.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2021

TactCapsNet: Tactile Capsule Network for Object Hardness Recognition.
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.
Proceedings of the 22nd IEEE International Conference on E-health Networking, 2020


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