Kungan Zeng

According to our database, Kungan Zeng authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A Spatiotemporal Information-Driven Cross-Attention Model With Sparse Representation for GNSS NLOS Signal Classification.

Kungan Zeng, Zhenni Li, Haoli Zhao, Kan Xie, Shengli Xie, Dusit Niyato, Wuhui Chen, Zibin Zheng

IEEE Internet Things J., October, 2024

Web service embedding: Representing the invocation association between services with practical-valued vectors.

Kungan Zeng, Incheon Paik

Expert Syst. Appl., March, 2024

A Few-Shot Learning-Based Semi-Supervised Method to Enhance NLOS Recognition Accuracy Across Multiple Locations by Cross-Spatiotemporal Information.

Kungan Zeng, Zhenni Li, Shengli Xie, Qianming Wang, Wuhui Chen, Zibin Zheng

IEEE Trans. Instrum. Meas., 2024

2023

Adaptive sparsity-regularized deep dictionary learning based on lifted proximal operator machine.

Zhenni Li, Ying Xie, Kungan Zeng, Shengli Xie, Banage T. G. S. Kumara

Knowl. Based Syst., 2023

2022

Web-based Automatic Deep Learning Service Generation System by Ontology Technologies.

Incheon Paik, Kungan Zeng, Munhan Bae

Proceedings of the 25th IEEE International Conference on Computational Science and Engineering, 2022

2021

Semantic Service Clustering With Lightweight BERT-Based Service Embedding Using Invocation Sequences.

Kungan Zeng, Incheon Paik

IEEE Access, 2021

Dynamic Service Recommendation Using Lightweight BERT-based Service Embedding in Edge Computing.

Kungan Zeng, Incheon Paik

Proceedings of the 14th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2021

2020

A Lightweight Transformer with Convolutional Attention.

Kungan Zeng, Incheon Paik

Proceedings of the 11th International Conference on Awareness Science and Technology, 2020

Web Service Composition Sequence Learning Based on Neural Language Networks.

Kungan Zeng, Incheon Paik

Proceedings of the 14th IEEE International Conference on Big Data Science and Engineering, 2020

Resolving Lexical Ambiguity in English-Japanese Neural Machine Translation.

Quang-Minh Do, Kungan Zeng, Incheon Paik

Proceedings of the AICCC 2020: 2020 3rd Artificial Intelligence and Cloud Computing Conference, 2020