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
- Xiaoming Tao (3 shared papers)Jianhua Lü (3 shared papers)Feifei Gao (2 shared papers)Guangyi Liu (1 shared paper)Xiang Peng (1 shared paper)Zhijin Qin (1 shared paper)Chengkang Pan (1 shared paper)Liang Zhang (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 347 citations
Danlan Huang's Hit Papers
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 181
- Computer Vision and Pattern Recognition 98
- Computer Networks and Communications 78
- Signal Processing 25
- Neurology 16
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 | 180 |
| 2 | 2021 | 111 | |
| 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 351 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (3 papers), Bluetooth and Wireless Communication Technologies (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Video Coding and Compression Technologies (1 paper), Energy Efficient Wireless Sensor Networks (1 paper), Indoor and Outdoor Localization Technologies (1 paper), Wireless Networks and Protocols (1 paper) and Wireless Signal Modulation Classification (1 paper). The work is most often cited by research in Artificial Intelligence (181 citations), Computer Vision and Pattern Recognition (98 citations), Computer Networks and Communications (78 citations), Signal Processing (25 citations) and Neurology (16 citations). Danlan Huang has collaborated with scholars based in China. Frequent co-authors include Xiaoming Tao, Jianhua Lü, Feifei Gao, Guangyi Liu, Xiang Peng, Zhijin Qin, Chengkang Pan, Liang Zhang, Jun Wan and Ting Jiang. 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.