Nan-I Wu

695 citations
13 papers · 510 · h-index 7

Impact in

    • Advanced Steganography and Watermarking Techniques
    • Chaos-based Image/Signal Encryption
    • Digital Media Forensic Detection
    • Advanced Data Compression Techniques
    • Advanced Image and Video Retrieval Techniques
    • Biometric Identification and Security

Papers in

Nan-I Wu

11 papers receiving 437 citations

Peers

Nan-I Wu
Comparison fields: 5 of 17
  • Computer Vision and Pattern Recognition 500
  • Signal Processing 20
  • Media Technology 12
  • Computational Theory and Mathematics 12
  • Artificial Intelligence 19
Replace Gangqiang Xiong with:
Gangqiang Xiong China
Jun-Chou Chuang Taiwan
Kaimeng Chen China
Brendan Halloran Australia
Wenguang He China
Joost van Beusekom Germany
Rupali Bhardwaj India
Ying‐Hsuan Huang Taiwan
Andreas Westfeld Germany
Nan-I Wu relative to Gangqiang Xiong China Gangqiang Xiong's profile →
Citations per field
00.5×11×
Gangqiang Xiong · 1×
Citations per year

Countries citing papers authored by Nan-I Wu

Since Specialization
Citations

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

Fields of papers citing papers by Nan-I Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nan-I Wu. 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 Nan-I Wu. The network helps show where Nan-I Wu may publish in the future.

Co-authors

The 8 scholars most cited alongside Nan-I Wu, 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 Nan-I Wu Line = papers co-authored together Nan-I Wu links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2007262
2
Data Hiding: Current Status and Key Issues
2007104
3 201132
4 201032
5
(Journal of Systems and Software, 81(1):150-158)A high quality steganographic method with pixel-value differencing and modulus function
200831
6 201727
7 201711
8 20235
9 20233
10 20232
11 20251
12 20250
13 20250

About Nan-I Wu

Nan-I Wu is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence, Health Information Management and Control and Systems Engineering, having authored 13 papers that have together received 510 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (10 papers), Chaos-based Image/Signal Encryption (9 papers), Digital Media Forensic Detection (8 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Quantum-Dot Cellular Automata (1 paper), Educational Research and Pedagogy (1 paper), Security in Wireless Sensor Networks (1 paper) and Energy Efficient Wireless Sensor Networks (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (500 citations), Signal Processing (20 citations), Media Technology (12 citations), Computational Theory and Mathematics (12 citations) and Artificial Intelligence (19 citations). Nan-I Wu has collaborated with scholars based in Taiwan, Indonesia and China. Frequent co-authors include Min‐Shiang Hwang, Chung-Ming Wang, Chwei‐Shyong Tsai, Kuo-Chen Wu, Der‐Chyuan Lou, Shu‐Fen Chiou, Iuon‐Chang Lin and Cheng‐Ying Yang. Their work appears in journals such as Journal of Systems and Software, Applied Sciences, Displays, Electronics and Applied Soft Computing.

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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