Fangwen Yu

Orcid: 0000-0001-7031-4185

According to our database1, Fangwen Yu authored at least 15 papers between 2016 and 2024.

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

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
ORB-NeuroSLAM: A Brain-Inspired 3-D SLAM System Based on ORB Features.
IEEE Internet Things J., April, 2024

NeuroVE: Brain-inspired Linear-Angular Velocity Estimation with Spiking Neural Networks.
CoRR, 2024

2023
A Neuro-Inspired Positioning System Integrating MEMS Sensors and DTMB Signals.
IEEE Trans. Broadcast., September, 2023

Editorial: Brain-inspired navigation and sensing for robots.
Frontiers Neurorobotics, June, 2023

Camera Frame Misalignment in a Teleoperated Eye-in-Hand Robot: Effects and a Simple Correction Method.
IEEE Trans. Hum. Mach. Syst., 2023

Brain-inspired multimodal hybrid neural network for robot place recognition.
Sci. Robotics, 2023

2022
Neuromorphic computing chip with spatiotemporal elasticity for multi-intelligent-tasking robots.
Sci. Robotics, 2022

MDOE: A Spatiotemporal Event Representation Considering the Magnitude and Density of Events.
IEEE Robotics Autom. Lett., 2022

Spike-Based Spatiotemporal Processing Enabled by Oscillation Neuron for Energy-Efficient Artificial Sensory Systems.
Adv. Intell. Syst., 2022

2021
A Plane-Dependent Model of 3D Grid Cells for Representing Both 2D and 3D Spaces Under Various Navigation Modes.
Frontiers Comput. Neurosci., 2021

EventDrop: Data Augmentation for Event-based Learning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2019
NeuroSLAM: a brain-inspired SLAM system for 3D environments.
Biol. Cybern., 2019

2016
iGeoNoti: A fine-grained indoor geo-notification system.
Proceedings of the 2016 Fourth International Conference on Ubiquitous Positioning, 2016

Sensory landmarks for indoor localization.
Proceedings of the 2016 Fourth International Conference on Ubiquitous Positioning, 2016

Error Decomposition Algorithm for Approximating the k-Error Linear Complexity of Periodic Sequences.
Proceedings of the 2016 IEEE Trustcom/BigDataSE/ISPA, 2016


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