Guipeng Lan

440 citations
23 papers · 292 · h-index 11

Impact in

Papers in

    • Digital Media Forensic Detection 7
    • Generative Adversarial Networks and Image Synthesis 6
    • Face recognition and analysis 6
    • Advanced Steganography and Watermarking Techniques 2
    • Visual Attention and Saliency Detection 2
    • Machine Learning in Healthcare 2
    • Anomaly Detection Techniques and Applications 2

Guipeng Lan

18 papers receiving 289 citations

Peers

Guipeng Lan
Comparison fields: 5 of 68
  • Computer Vision and Pattern Recognition 177
  • Signal Processing 24
  • Media Technology 18
  • Artificial Intelligence 64
  • Health Informatics 2
Replace Srishti Srivastava with:
Srishti Srivastava United States
Keyang Cheng China
Yogesh Dandawate India
Hiroki Ohashi Japan
G. Yamuna India
Zhuang Li China
Wujian Ye China
Krishna Teja Chitty-Venkata United States
Gungor Polatkan United States
Jiwei Zhang China
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Citations per field
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Srishti Srivastava · 1×
Citations per year

Countries citing papers authored by Guipeng Lan

Since Specialization
Citations

This map shows the geographic impact of Guipeng Lan'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 Guipeng Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guipeng Lan more than expected).

Fields of papers citing papers by Guipeng Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guipeng Lan. 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 Guipeng Lan. The network helps show where Guipeng Lan may publish in the future.

Co-authors

The 20 scholars most cited alongside Guipeng Lan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Guipeng Lan Line = papers co-authored together Guipeng Lan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

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About Guipeng Lan

Guipeng Lan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Cognitive Neuroscience and Media Technology, having authored 23 papers that have together received 292 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (7 papers), Generative Adversarial Networks and Image Synthesis (6 papers), Face recognition and analysis (6 papers), Machine Learning in Healthcare (2 papers), Anomaly Detection Techniques and Applications (2 papers), Advanced Steganography and Watermarking Techniques (2 papers), Visual Attention and Saliency Detection (2 papers) and Aesthetic Perception and Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (177 citations), Signal Processing (24 citations), Media Technology (18 citations), Artificial Intelligence (64 citations) and Health Informatics (2 citations). Guipeng Lan has collaborated with scholars based in China, United Kingdom and Saudi Arabia. Frequent co-authors include Shuai Xiao, Jiachen Yang, Jiabao Wen, Zhuo Zhang, Yang Li, Aiyun Li, Huihui Wang, Xinbo Gao, Wen Lu and Sezai Erċışlı. Their work appears in journals such as IEEE Transactions on Multimedia, IEEE Journal of Biomedical and Health Informatics, Sensors, Expert Systems with Applications and IEEE Transactions on Broadcasting.

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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