Tze-Yang Tung

924 total citations · 2 hit papers
18 papers, 589 citations indexed

About

Tze-Yang Tung is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Tze-Yang Tung has authored 18 papers receiving a total of 589 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 6 papers in Electrical and Electronic Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Tze-Yang Tung's work include Sparse and Compressive Sensing Techniques (4 papers), Advanced Data Compression Techniques (4 papers) and Molecular Communication and Nanonetworks (3 papers). Tze-Yang Tung is often cited by papers focused on Sparse and Compressive Sensing Techniques (4 papers), Advanced Data Compression Techniques (4 papers) and Molecular Communication and Nanonetworks (3 papers). Tze-Yang Tung collaborates with scholars based in United Kingdom, United States and China. Tze-Yang Tung's co-authors include Denız Gündüz, Mikołaj Jankowski, David Burth Kurka, Pier Luigi Dragotti, Bo Ai, Mahdi Boloursaz Mashhadi, Wei Chen, Jialong Xu, Yuxuan Sun and Urbashi Mitra and has published in prestigious journals such as Proceedings of the IEEE, IEEE Journal on Selected Areas in Communications and IEEE Communications Magazine.

In The Last Decade

Tze-Yang Tung

18 papers receiving 584 citations

Hit Papers

DeepWiVe: Deep-Learning-Aided Wireless Video Transmission 2022 2026 2023 2024 2022 2023 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. DeepWiVe: Deep-Learning-Aided Wireless Video Transmission
    2022 119 citations Tze-Yang Tung, Denız Gündüz IEEE Journal on Selected Areas in Communications profile →
  2. Generative Joint Source-Channel Coding for Semantic Image Transmission
    2023 84 citations Tze-Yang Tung, Pier Luigi Dragotti et al. IEEE Journal on Selected Areas in Communications profile →

Peers

Tze-Yang Tung
Iñaki Estella Aguerri France
Zhenzi Weng United Kingdom
Peiwen Jiang China
Ang Yang China
Mikołaj Jankowski United Kingdom
Xue Lin China
Kyle Rupnow United States
Daeseon Choi South Korea
Weihong Xu United States
Qiao Tian China
Iñaki Estella Aguerri France
Tze-Yang Tung
Citations per year, relative to Tze-Yang Tung Tze-Yang Tung (= 1×) peers Iñaki Estella Aguerri

Countries citing papers authored by Tze-Yang Tung

Since Specialization
Citations

This map shows the geographic impact of Tze-Yang Tung's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tze-Yang Tung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tze-Yang Tung more than expected).

Fields of papers citing papers by Tze-Yang Tung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tze-Yang Tung. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tze-Yang Tung. The network helps show where Tze-Yang Tung may publish in the future.

Co-authorship network of co-authors of Tze-Yang Tung

This figure shows the co-authorship network connecting the top 25 collaborators of Tze-Yang Tung. A scholar is included among the top collaborators of Tze-Yang Tung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tze-Yang Tung. Tze-Yang Tung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Tung, Tze-Yang, et al.. (2025). Multi-Level Reliability Interface for Semantic Communications Over Wireless Networks. IEEE Transactions on Communications. 73(8). 6023–6035. 1 indexed citations
2.
Liao, Qi & Tze-Yang Tung. (2024). AdaSem: Adaptive Goal-Oriented Semantic Communications for End-to-End Camera Relocalization. 1111–1120. 2 indexed citations
3.
Gündüz, Denız, Michèle A. Wigger, Tze-Yang Tung, Ping Zhang, & Yong Xiao. (2024). Joint Source–Channel Coding: Fundamentals and Recent Progress in Practical Designs. Proceedings of the IEEE. 113(9). 888–919. 8 indexed citations
4.
Tung, Tze-Yang, et al.. (2023). Generative Joint Source-Channel Coding for Semantic Image Transmission. IEEE Journal on Selected Areas in Communications. 41(8). 2645–2657. 84 indexed citations breakdown →
5.
Xu, Jialong, Tze-Yang Tung, Bo Ai, et al.. (2023). Deep Joint Source-Channel Coding for Semantic Communications. IEEE Communications Magazine. 61(11). 42–48. 57 indexed citations
6.
Tung, Tze-Yang & Denız Gündüz. (2023). Deep Joint Source-Channel and Encryption Coding: Secure Semantic Communications. 5620–5625. 42 indexed citations
7.
Tung, Tze-Yang, et al.. (2023). Goal-oriented Compression with a Constrained Decoder. 868–873. 3 indexed citations
8.
Tung, Tze-Yang, David Burth Kurka, Mikołaj Jankowski, & Denız Gündüz. (2022). DeepJSCC-Q: Constellation Constrained Deep Joint Source-Channel Coding. IEEE Journal on Selected Areas in Information Theory. 3(4). 720–731. 81 indexed citations
9.
Tung, Tze-Yang & Denız Gündüz. (2022). DeepWiVe: Deep-Learning-Aided Wireless Video Transmission. IEEE Journal on Selected Areas in Communications. 40(9). 2570–2583. 119 indexed citations breakdown →
10.
Tung, Tze-Yang & Denız Gündüz. (2022). Deep-Learning-Aided Wireless Video Transmission. IRIS UNIMORE (University of Modena and Reggio Emilia). 1–5. 7 indexed citations
11.
Tung, Tze-Yang, David Burth Kurka, Mikołaj Jankowski, & Denız Gündüz. (2022). DeepJSCC-Q: Channel Input Constrained Deep Joint Source-Channel Coding. ICC 2022 - IEEE International Conference on Communications. 3880–3885. 21 indexed citations
12.
Mashhadi, Mahdi Boloursaz, et al.. (2021). . View. 49 indexed citations
13.
Tung, Tze-Yang, et al.. (2021). Effective Communications: A Joint Learning and Communication Framework for Multi-Agent Reinforcement Learning over Noisy Channels. Iris Unimore (University of Modena and Reggio Emilia). 80 indexed citations
14.
Tung, Tze-Yang, et al.. (2021). Context-Aware Effective Communications. 2021 55th Asilomar Conference on Signals, Systems, and Computers. 334–339. 3 indexed citations
15.
Tung, Tze-Yang & Urbashi Mitra. (2019). Robust Molecular Communications: DFE-SPRTs and Synchronisation. 1–6. 1 indexed citations
16.
Tung, Tze-Yang & Urbashi Mitra. (2019). Synchronization Error Robust Transceivers for Molecular Communication. IEEE Transactions on Molecular Biological and Multi-Scale Communications. 5(3). 207–221. 11 indexed citations
17.
Tung, Tze-Yang & Denız Gündüz. (2018). SparseCast: Hybrid Digital-Analog Wireless Image Transmission Exploiting Frequency-Domain Sparsity. IEEE Communications Letters. 22(12). 2451–2454. 19 indexed citations
18.
Tung, Tze-Yang & Urbashi Mitra. (2018). Increasing Robustness to Synchronisation Errors in Molecular Communications. 1–5. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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