Massimo Iuliani
Impact in
-
- Digital Media Forensic Detection
- Advanced Steganography and Watermarking Techniques
- Generative Adversarial Networks and Image Synthesis
- Video Analysis and Summarization
- Law top 1%
- Law in Society and Culture
Papers in
-
- Digital Media Forensic Detection 24
- Advanced Steganography and Watermarking Techniques 22
- Generative Adversarial Networks and Image Synthesis 1
- Law 10
- Law in Society and Culture 10
- Co-authors
- Alessandro Piva (24 shared papers)Dasara Shullani (12 shared papers)Marco Fontani (5 shared papers)Marco Fanfani (4 shared papers)Carlo Colombo (4 shared papers)Fabio Bellavia (3 shared papers)Manuel M. Oliveira (1 shared paper)Pengpeng Yang (1 shared paper)
In The Last Decade
Massimo Iuliani
23 papers receiving 428 citations
Peers
Comparison fields: 5 of 41
- Computer Vision and Pattern Recognition 412
- Law 90
- Media Technology 70
- Space and Planetary Science 9
- Biophysics 23
Countries citing papers authored by Massimo Iuliani
This map shows the geographic impact of Massimo Iuliani'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 Massimo Iuliani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Iuliani more than expected).
Fields of papers citing papers by Massimo Iuliani
This network shows the impact of papers produced by Massimo Iuliani. 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 Massimo Iuliani. The network helps show where Massimo Iuliani may publish in the future.
Co-authors
The 22 scholars most cited alongside Massimo Iuliani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 177 | |
| 2 | 2019 | 42 | |
| 3 | 2018 | 31 | |
| 4 | 2021 | 29 | |
| 5 | 2020 | 24 | |
| 6 | 2015 | 20 | |
| 7 | 2019 | 15 | |
| 8 | 2017 | 13 | |
| 9 | 2022 | 13 | |
| 10 | 2020 | 8 | |
| 11 | 2022 | 8 | |
| 12 | 2021 | 8 | |
| 13 | 2019 | 8 | |
| 14 | 2014 | 6 | |
| 15 | 2023 | 5 | |
| 16 | 2019 | 5 | |
| 17 | 2014 | 5 | |
| 18 | 2021 | 5 | |
| 19 | 2024 | 4 | |
| 20 | 2016 | 4 |
About Massimo Iuliani
Massimo Iuliani is a scholar working on Computer Vision and Pattern Recognition, Law, Information Systems, Artificial Intelligence and Signal Processing, having authored 24 papers that have together received 435 indexed citations. Recurring topics across this work include Digital Media Forensic Detection (24 papers), Advanced Steganography and Watermarking Techniques (22 papers), Law in Society and Culture (10 papers), Digital and Cyber Forensics (3 papers), Cell Image Analysis Techniques (2 papers), Misinformation and Its Impacts (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Authorship Attribution and Profiling (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (412 citations), Law (90 citations), Media Technology (70 citations), Space and Planetary Science (9 citations) and Biophysics (23 citations). Massimo Iuliani has collaborated with scholars based in Italy, Brazil and China. Frequent co-authors include Alessandro Piva, Dasara Shullani, Marco Fontani, Marco Fanfani, Carlo Colombo, Fabio Bellavia, Manuel M. Oliveira, Pengpeng Yang, Pasquale Ferrara and Yao Zhao. Their work appears in journals such as IEEE Access, Journal of Visual Communication and Image Representation, IEEE Journal of Selected Topics in Signal Processing, Computers & Graphics and IEEE Transactions on Information Forensics and Security.
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.