Francesco Cricri
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Sociology and Political Science
- Computer Networks and Communications
- Co-authors
- Honglei ZhangEsa RahtuEmre AksuIgor D. D. CurcioHamed R. TavakoliÇağlar AytekinMiska M. HannukselaMoncef Gabbouj
- Topics
- Advanced Image Processing Techniques (16 papers)Image and Signal Denoising Methods (10 papers)Advanced Data Compression Techniques (10 papers)
In The Last Decade
Francesco Cricri
36 papers receiving 462 citations
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 375
- Signal Processing 126
- Artificial Intelligence 93
- Sociology and Political Science 34
- Computer Networks and Communications 26
Countries citing papers authored by Francesco Cricri
This map shows the geographic impact of Francesco Cricri'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 Francesco Cricri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Cricri more than expected).
Fields of papers citing papers by Francesco Cricri
This network shows the impact of papers produced by Francesco Cricri. 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 Francesco Cricri. The network helps show where Francesco Cricri may publish in the future.
Co-authorship network of co-authors of Francesco Cricri
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Cricri. A scholar is included among the top collaborators of Francesco Cricri 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 Francesco Cricri. Francesco Cricri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 75 | |
| 10 | 33 | |
| 11 | 2 | |
| 12 | 7 | |
| 13 | 15 | |
| 14 | Compressing Weight-updates for Image Artifacts Removal Neural Networks | 1 |
| 15 | A Compression Objective and a Cycle Loss for Neural Image Compression | 2 |
| 16 | Block-optimized Variable Bit Rate Neural Image Compression | 3 |
| 17 | 60 | |
| 18 | 27 | |
| 19 | Sensor-based analysis of user generated video for multi-camera video remixing | 1 |
| 20 | 21 |
About Francesco Cricri
Francesco Cricri is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Human-Computer Interaction, having authored 42 papers that have together received 478 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (16 papers), Image and Signal Denoising Methods (10 papers) and Advanced Data Compression Techniques (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (375 citations), Signal Processing (126 citations) and Human-Computer Interaction (18 citations). Francesco Cricri has collaborated with scholars based in Finland, Austria and Germany. Frequent co-authors include Honglei Zhang, Esa Rahtu, Emre Aksu, Igor D. D. Curcio, Hamed R. Tavakoli, Çağlar Aytekin, Miska M. Hannuksela, Moncef Gabbouj, Lixin Fan and Yanlin Qian. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia and Multimedia Tools and Applications.
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.