Ignazio Pillai
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Co-authors
- Fabio RoliGiorgio FumeraBattista BiggioSamuel Rota BulòMarcello PelilloDavide AriuRiccardo Satta
- Topics
- Spam and Phishing Detection (12 papers)Text and Document Classification Technologies (6 papers)Advanced Steganography and Watermarking Techniques (5 papers)
- Journals
- Pattern RecognitionIEEE Transactions on Neural Networks and Learning SystemsJournal of Machine Learning Research
- Partner nations
- Italy
In The Last Decade
Ignazio Pillai
13 papers receiving 442 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 369
- Information Systems 230
- Computer Vision and Pattern Recognition 133
- Computer Networks and Communications 115
- Signal Processing 100
Countries citing papers authored by Ignazio Pillai
This map shows the geographic impact of Ignazio Pillai'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 Ignazio Pillai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ignazio Pillai more than expected).
Fields of papers citing papers by Ignazio Pillai
This network shows the impact of papers produced by Ignazio Pillai. 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 Ignazio Pillai. The network helps show where Ignazio Pillai may publish in the future.
Co-authorship network of co-authors of Ignazio Pillai
This figure shows the co-authorship network connecting the top 25 collaborators of Ignazio Pillai. A scholar is included among the top collaborators of Ignazio Pillai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ignazio Pillai. Ignazio Pillai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 40 | |
| 2 | 55 | |
| 3 | 67 | |
| 4 | 31 | |
| 5 | 38 | |
| 6 | 61 | |
| 7 | Improving Image Spam Filtering Using Image Text Features. | 11 |
| 8 | 32 | |
| 9 | Image spam filtering by detection of adversarial obfuscated text | 1 |
| 10 | Image Spam Filtering by Content Obscuring Detection | 26 |
| 11 | 22 | |
| 12 | EVADING SPAMASSASSIN WITH OBFUSCATED TEXT IMAGES | 1 |
| 13 | Spam Filtering Based On The Analysis Of Text Information Embedded Into Images | 88 |
| 14 | 12 |
About Ignazio Pillai
Ignazio Pillai is a scholar working on Information Systems, Signal Processing and Artificial Intelligence, having authored 14 papers that have together received 485 indexed citations. Recurring topics across this work include Spam and Phishing Detection (12 papers), Text and Document Classification Technologies (6 papers) and Advanced Steganography and Watermarking Techniques (5 papers). The work is most often cited by research in Artificial Intelligence (369 citations), Information Systems (230 citations) and Signal Processing (100 citations). Ignazio Pillai has collaborated with scholars based in Italy. Frequent co-authors include Fabio Roli, Giorgio Fumera, Battista Biggio, Samuel Rota Bulò, Marcello Pelillo, Davide Ariu and Riccardo Satta. Their work appears in journals such as Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems and Journal of Machine Learning Research.
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.