Xianfeng Yuan

According to our database1, Xianfeng Yuan authored at least 15 papers between 2014 and 2021.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2021
Multi-Scale Capsule Attention Network and Joint Distributed Optimal Transport for Bearing Fault Diagnosis under Different Working Loads.
Sensors, 2021

Scene image and human skeleton-based dual-stream human action recognition.
Pattern Recognit. Lett., 2021

Random mask-based estimation of the distribution algorithm for stacked auto-encoder one-step pre-training.
Comput. Ind. Eng., 2021

2020
Underwater Fish Body Length Estimation Based on Binocular Image Processing.
Inf., 2020

Grey wolf optimizer with an enhanced hierarchy and its application to the wireless sensor network coverage optimization problem.
Appl. Soft Comput., 2020

I3D-Shufflenet Based Human Action Recognition.
Algorithms, 2020

2019
Improved Chaotic Particle Swarm Optimization Algorithm with More Symmetric Distribution for Numerical Function Optimization.
Symmetry, 2019

Real-Time Photometric Calibrated Monocular Direct Visual SLAM.
Sensors, 2019

Hybrid particle swarm optimization with spiral-shaped mechanism for feature selection.
Expert Syst. Appl., 2019

Fault Diagnosis of Analog Circuits Based on IH-PSO Optimized Support Vector Machine.
IEEE Access, 2019

An Modified Real-time Photometric Calibration Algorithm Based on ORB Features.
Proceedings of the 2019 IEEE International Conference on Robotics and Biomimetics, 2019

2016
A high precision visual localization sensor and its working methodology for an indoor mobile robot.
Frontiers Inf. Technol. Electron. Eng., 2016

2015
A Novel Fast Training Method for SVM and Its Application in Fault Diagnosis of Service Robot.
Int. J. Online Eng., 2015

A Novel Mittag-Leffler Kernel Based Hybrid Fault Diagnosis Method for Wheeled Robot Driving System.
Comput. Intell. Neurosci., 2015

2014
Real-time action recognition based on a modified Deep Belief Network model.
Proceedings of the IEEE International Conference on Information and Automation, 2014


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