Xiaofeng Song
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- Advanced Steganography and Watermarking Techniques 17
- Digital Media Forensic Detection 16
- Chaos-based Image/Signal Encryption 12
- Face recognition and analysis 4
- Face and Expression Recognition 4
- Image and Video Stabilization 3
- Media Technology top 10%
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- Biometric Identification and Security 4
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- Combustion and Detonation Processes 2
- Co-authors
- Chunfang YangFenlin LiuXiangyang LuoYi ZhangXiaolong LiWeiming ZhangYuan LiuPing Wang
In The Last Decade
Xiaofeng Song
27 papers receiving 401 citations
Peers
Comparison fields: 5 of 47
- Computer Vision and Pattern Recognition 379
- Media Technology 27
- Signal Processing 21
- Artificial Intelligence 57
- Computer Graphics and Computer-Aided Design 3
Countries citing papers authored by Xiaofeng Song
This map shows the geographic impact of Xiaofeng Song'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 Xiaofeng Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaofeng Song more than expected).
Fields of papers citing papers by Xiaofeng Song
This network shows the impact of papers produced by Xiaofeng Song. 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 Xiaofeng Song. The network helps show where Xiaofeng Song may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaofeng Song, 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 | 2024 | 1 | |
| 2 | 2024 | 17 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 1 | |
| 5 | 2022 | 7 | |
| 6 | 2021 | 22 | |
| 7 | 2021 | 0 | |
| 8 | 2020 | 10 | |
| 9 | 2020 | 18 | |
| 10 | 2019 | 0 | |
| 11 | 2018 | 1 | |
| 12 | 2017 | 1 | |
| 13 | 2016 | 3 | |
| 14 | 2016 | 21 | |
| 15 | 2015 | 59 | |
| 16 | 2015 | 1 | |
| 17 | 2014 | 8 | |
| 18 | 2012 | 1 | |
| 19 | THE OPTIMIZED SUPPORT VECTOR MACHINE WITH CORRELATIVE FEATURES FOR CLASSIFICATION OF NATURAL SPEARMINT ESSENCE | 2010 | 4 |
| 20 | 2010 | 1 |
About Xiaofeng Song
Xiaofeng Song is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 32 papers that have together received 418 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (17 papers), Digital Media Forensic Detection (16 papers), Chaos-based Image/Signal Encryption (12 papers), Biometric Identification and Security (4 papers), Face recognition and analysis (4 papers), Face and Expression Recognition (4 papers), Image and Video Stabilization (3 papers) and Combustion and Detonation Processes (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (379 citations), Media Technology (27 citations) and Signal Processing (21 citations). Xiaofeng Song has collaborated with scholars based in China and Germany. Frequent co-authors include Chunfang Yang, Fenlin Liu, Xiangyang Luo, Yi Zhang, Xiaolong Li, Weiming Zhang, Yuan Liu, Ping Wang, Kun Han and Bin Jiang. Their work appears in journals such as Multimedia Tools and Applications, International Communications in Heat and Mass Transfer, IEEE Geoscience and Remote Sensing Letters, International journal of innovative computing, information & control and Neural Computing and Applications.
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.