Ping Li

Affiliations:
  • Zhejiang University, Institute of Industrial Process Control, Hangzhou, China


According to our database1, Ping Li authored at least 29 papers between 2000 and 2022.

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

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2022
A Visual Compass Based on Point and Line Features for UAV High-Altitude Orientation Estimation.
Remote. Sens., 2022

RGB-D SLAM in Dynamic Environments Using Point Correlations.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

2020
Novel 3D point set registration method based on regionalized Gaussian process map reconstruction.
Frontiers Inf. Technol. Electron. Eng., 2020

Correction to: GP-SLAM: laser-based SLAM approach based on regionalized Gaussian process map reconstruction.
Auton. Robots, 2020

GP-SLAM: laser-based SLAM approach based on regionalized Gaussian process map reconstruction.
Auton. Robots, 2020

2019
Uncalibrated downward-looking UAV visual compass based on clustered point features.
Sci. China Inf. Sci., 2019

Multi-Spectral Visual Odometry without Explicit Stereo Matching.
Proceedings of the 2019 International Conference on 3D Vision, 2019

2018
Transferring knowledge from human-demonstration trajectories to reinforcement learning.
Trans. Inst. Meas. Control, 2018

RGB-D SLAM in Dynamic Environments Using Points Correlations.
CoRR, 2018

Integrated probabilistic modeling method for transient opening height prediction of check valves in oil-gas multiphase pumps.
Adv. Eng. Softw., 2018

Hybrid model for discharge flow rate prediction of reciprocating multiphase pumps.
Adv. Eng. Softw., 2018

Feature Regions Segmentation Based RGB-D Visual Odometry in Dynamic Environment.
Proceedings of the IECON 2018, 2018

2017
Whole flow field performance prediction by impeller parameters of centrifugal pumps using support vector regression.
Adv. Eng. Softw., 2017

2016
A novel biologically inspired ELM-based network for image recognition.
Neurocomputing, 2016

Integrating symmetry of environment by designing special basis functions for value function approximation in reinforcement learning.
Proceedings of the 14th International Conference on Control, 2016

2013
Symmetric extreme learning machine.
Neural Comput. Appl., 2013

2012
A comparative analysis of support vector machines and extreme learning machines.
Neural Networks, 2012

2008
Grey-box modeling of a small-scale helicopter using physical knowledge and Bayesian Techniques.
Proceedings of the 10th International Conference on Control, 2008

2006
Fuzzy Support Vector Clustering.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

Grid-Based Fuzzy Support Vector Data Description.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

Adaptive Kernel Leaning Networks with Application to Nonlinear System Identification.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

2005
Soft Sensor Modeling Based on DICA-SVR.
Proceedings of the Advances in Intelligent Computing, 2005

2004
PLS-based optimal quality control model for TE process.
Proceedings of the IEEE International Conference on Systems, 2004

2003
Rough set based modeling and controller design in an internal model control system.
Proceedings of the IEEE International Conference on Systems, 2003

Quality monitoring of the rubber mixing process by using the discounted-measurement RPLS algorithm.
Proceedings of the IEEE International Conference on Systems, 2003

Study of discharge modeling method using support vector machine for rubber mixing process.
Proceedings of the American Control Conference, 2003

2002
Understanding PCA fault detection results by using expectation analysis method.
Proceedings of the 41st IEEE Conference on Decision and Control, 2002

2000
Improved PCA with optimized sensor locations for process monitoring and fault diagnosis.
Proceedings of the 39th IEEE Conference on Decision and Control, 2000

Wavelet-based frequency band weighting approach to control-relevant process identification.
Proceedings of the American Control Conference, 2000


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