Yujun Zeng

Orcid: 0000-0002-5765-684X

According to our database1, Yujun Zeng authored at least 14 papers between 2015 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Patch-Mixing Contrastive Regularization for Few-Label Semi-Supervised Learning.
IEEE Trans. Artif. Intell., January, 2024

2023
A Feature Saliency Based Hybrid Neural Network Model for Object Recognition.
Proceedings of the 6th International Conference on Machine Learning and Machine Intelligence, 2023

2022
Transfer reinforcement learning via meta-knowledge extraction using auto-pruned decision trees.
Knowl. Based Syst., 2022

Synchronous Maneuver Searching and Trajectory Planning for Autonomous Vehicles in Dynamic Traffic Environments.
IEEE Intell. Transp. Syst. Mag., 2022

Target-driven visual navigation in indoor scenes using reinforcement learning and imitation learning.
CAAI Trans. Intell. Technol., 2022

2021
Application of Flipped Classroom Model Driven by Big Data and Neural Network in Oral English Teaching.
Wirel. Commun. Mob. Comput., 2021

Robust semi-supervised classification based on data augmented online ELMs with deep features.
Knowl. Based Syst., 2021

Efficient Reinforcement Learning from Demonstration via Bayesian Network-Based Knowledge Extraction.
Comput. Intell. Neurosci., 2021

Data-efficient Deep Reinforcement Learning Method Toward Scaling Continuous Robotic Task with Sparse Rewards.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2021

Accelerating Deep Reinforcement Learning via Hierarchical State Encoding with ELMs.
Proceedings of the Intelligent Computing Theories and Application, 2021

2019
Reply to "Comments on 'Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features"'.
IEEE Trans. Intell. Transp. Syst., 2019

2018
Evolutionary Hierarchical Sparse Extreme Learning Autoencoder Network for Object Recognition.
Symmetry, 2018

2017
Traffic Sign Recognition Using Kernel Extreme Learning Machines With Deep Perceptual Features.
IEEE Trans. Intell. Transp. Syst., 2017

2015
Traffic Sign Recognition Using Deep Convolutional Networks and Extreme Learning Machine.
Proceedings of the Intelligence Science and Big Data Engineering. Image and Video Data Engineering, 2015


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