Gabriele Fanelli
- Computer Vision and Pattern Recognition top 1%
- Human-Computer Interaction top 2%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Co-authors
- Jüergen GallLuc Van GoolMatthias DantoneAndrea FossatiAngela YaoThibaut WeiseMarco FratarcangeliAhmed Hussen Abdelaziz
- Topics
- Face recognition and analysis (9 papers)Speech and Audio Processing (5 papers)Face and Expression Recognition (5 papers)
- Journals
- International Journal of Computer VisionIEEE Transactions on MultimediaIRIS Research product catalog (Sapienza University of Rome)
- Partner nations
- SwitzerlandUnited StatesGermany
In The Last Decade
Gabriele Fanelli
11 papers receiving 923 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Computer Vision and Pattern Recognition 803
- Human-Computer Interaction 198
- Signal Processing 128
- Artificial Intelligence 128
- Biomedical Engineering 82
Countries citing papers authored by Gabriele Fanelli
This map shows the geographic impact of Gabriele Fanelli'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 Gabriele Fanelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriele Fanelli more than expected).
Fields of papers citing papers by Gabriele Fanelli
This network shows the impact of papers produced by Gabriele Fanelli. 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 Gabriele Fanelli. The network helps show where Gabriele Fanelli may publish in the future.
Co-authorship network of co-authors of Gabriele Fanelli
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriele Fanelli. A scholar is included among the top collaborators of Gabriele Fanelli 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 Gabriele Fanelli. Gabriele Fanelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 38 | |
| 3 | Random Forests for Real Time 3D Face Analysisbreakdown → | 367 |
| 4 | 16 | |
| 5 | 300 | |
| 6 | 126 | |
| 7 | Towards Kinect-based wheelchair user behavior analysis | 1 |
| 8 | 91 | |
| 9 | Acquisition of a 3D audio-visual corpus of affective speech | 5 |
| 10 | 3D Vision Technology for Capturing Multimodal Corpora: Chances and Challenges | 5 |
| 11 | 7 | |
| 12 | 5 |
About Gabriele Fanelli
Gabriele Fanelli is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Human-Computer Interaction, having authored 12 papers that have together received 970 indexed citations. Recurring topics across this work include Face recognition and analysis (9 papers), Speech and Audio Processing (5 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (803 citations), Human-Computer Interaction (198 citations) and Signal Processing (128 citations). Gabriele Fanelli has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Jüergen Gall, Luc Van Gool, Matthias Dantone, Andrea Fossati, Luc Van Gool, Angela Yao, Thibaut Weise, Marco Fratarcangeli, Luc Van Gool and Ahmed Hussen Abdelaziz. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Multimedia and IRIS Research product catalog (Sapienza University of Rome).
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.