Danlan Huang
Impact in
- Artificial Intelligence top 10%
- Wireless Signal Modulation Classification
- Cognitive Computing and Networks
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- Advanced Data Compression Techniques
- Advanced Image and Video Retrieval Techniques
- Digital Media Forensic Detection
Papers in
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- Digital Media Forensic Detection 3
- Advanced Image and Video Retrieval Techniques 1
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- Bluetooth and Wireless Communication Technologies 2
- Energy Efficient Wireless Sensor Networks 1
- Wireless Networks and Protocols 1
- Co-authors
- Jianhua Lü (3 shared papers)Xiaoming Tao (3 shared papers)Feifei Gao (2 shared papers)Chengkang Pan (1 shared paper)Xiang Peng (1 shared paper)Zhijin Qin (1 shared paper)Guangyi Liu (1 shared paper)Jun Wan (1 shared paper)
- Journals
- IEEE Journal on Selected Areas in Communications (1 paper)2021 IEEE Global Communications Conference (GLOBECOM) (1 paper)GLOBECOM 2022 - 2022 IEEE Global Communications Conference (1 paper)
- Partner nations
- China
In The Last Decade
Danlan Huang
4 papers receiving 362 citations
Danlan Huang's Hit Papers
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 184
- Computer Vision and Pattern Recognition 101
- Computer Networks and Communications 79
- Signal Processing 25
- Neurology 17
Countries citing papers authored by Danlan Huang
This map shows the geographic impact of Danlan Huang'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 Danlan Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danlan Huang more than expected).
Fields of papers citing papers by Danlan Huang
This network shows the impact of papers produced by Danlan Huang. 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 Danlan Huang. The network helps show where Danlan Huang may publish in the future.
Co-authors
The 13 scholars most cited alongside Danlan Huang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Toward Semantic Communications: Deep Learning-Based Image Semantic Coding Hit paper breakdown → | 2022 | 189 |
| 2 | 2021 | 115 | |
| 3 | 2022 | 59 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 0 |
About Danlan Huang
Danlan Huang is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Sociology and Political Science, Signal Processing and Artificial Intelligence, having authored 6 papers that have together received 364 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (3 papers), Bluetooth and Wireless Communication Technologies (2 papers), Multimedia Communication and Technology (1 paper), Speech Recognition and Synthesis (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Energy Efficient Wireless Sensor Networks (1 paper), Video Coding and Compression Technologies (1 paper) and Wireless Networks and Protocols (1 paper). The work is most often cited by research in Artificial Intelligence (184 citations), Computer Vision and Pattern Recognition (101 citations), Computer Networks and Communications (79 citations), Signal Processing (25 citations) and Neurology (17 citations). Danlan Huang has collaborated with scholars based in China. Frequent co-authors include Jianhua Lü, Xiaoming Tao, Feifei Gao, Chengkang Pan, Xiang Peng, Zhijin Qin, Guangyi Liu, Jun Wan, Liang Zhang and Zhixin Qi. Their work appears in journals such as IEEE Journal on Selected Areas in Communications, 2021 IEEE Global Communications Conference (GLOBECOM) and GLOBECOM 2022 - 2022 IEEE Global Communications Conference.
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.