Francesca Odone

3.0k total citations
126 papers, 1.6k citations indexed

About

Francesca Odone is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Francesca Odone has authored 126 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Computer Vision and Pattern Recognition, 33 papers in Artificial Intelligence and 15 papers in Control and Systems Engineering. Recurrent topics in Francesca Odone's work include Human Pose and Action Recognition (29 papers), Advanced Image and Video Retrieval Techniques (28 papers) and Advanced Vision and Imaging (20 papers). Francesca Odone is often cited by papers focused on Human Pose and Action Recognition (29 papers), Advanced Image and Video Retrieval Techniques (28 papers) and Advanced Vision and Imaging (20 papers). Francesca Odone collaborates with scholars based in Italy, United States and United Kingdom. Francesca Odone's co-authors include Alessandro Verri, Annalisa Barla, Nicoletta Noceti, Ernesto De Vito, Lorenzo Rosasco, Francesco Isgrò, Emanuele Trucco, Christine De Mol, Maura Casadio and Andrea Caponnetto and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Francesca Odone

118 papers receiving 1.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Francesca Odone Italy 20 922 382 181 151 139 126 1.6k
Jing Pan China 20 914 1.0× 360 0.9× 201 1.1× 119 0.8× 146 1.1× 93 1.7k
Miguel Cazorla Spain 22 775 0.8× 261 0.7× 327 1.8× 118 0.8× 176 1.3× 136 1.7k
Luigi Cinque Italy 26 1.3k 1.4× 571 1.5× 169 0.9× 89 0.6× 119 0.9× 159 2.3k
Xavier Alameda-Pineda France 24 895 1.0× 582 1.5× 130 0.7× 101 0.7× 138 1.0× 69 2.0k
John Zelek Canada 19 922 1.0× 262 0.7× 339 1.9× 67 0.4× 133 1.0× 153 1.5k
Wei‐Yun Yau Singapore 28 1.9k 2.1× 549 1.4× 154 0.9× 87 0.6× 75 0.5× 151 3.1k
Jesse S. Jin Australia 25 1.2k 1.3× 241 0.6× 161 0.9× 42 0.3× 279 2.0× 126 2.3k
Wei Ji China 18 1.3k 1.4× 287 0.8× 115 0.6× 167 1.1× 185 1.3× 75 1.8k
Caroline Pantofaru United States 19 1.4k 1.5× 466 1.2× 217 1.2× 306 2.0× 93 0.7× 37 2.2k

Countries citing papers authored by Francesca Odone

Since Specialization
Citations

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

Fields of papers citing papers by Francesca Odone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francesca Odone. 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 Francesca Odone. The network helps show where Francesca Odone may publish in the future.

Co-authorship network of co-authors of Francesca Odone

This figure shows the co-authorship network connecting the top 25 collaborators of Francesca Odone. A scholar is included among the top collaborators of Francesca Odone 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 Francesca Odone. Francesca Odone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Manhardt, Fabian, et al.. (2025). View-to-label: Multi-view consistency for self-supervised monocular 3D object detection. Computer Vision and Image Understanding. 254. 104320–104320.
2.
Cellerino, Maria, et al.. (2025). Markerless Video-Based Gait Analysis in People With Multiple Sclerosis. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 33. 2743–2749. 1 indexed citations
3.
Odone, Francesca, et al.. (2024). Is In-Domain Data Beneficial in Transfer Learning for Landmarks Detection in X-Ray Images?. CINECA IRIS Institutial Research Information System (University of Genoa). 1–5. 2 indexed citations
4.
Pastore, Vito Paolo, et al.. (2024). A deep learning approach to direct immunofluorescence pattern recognition in autoimmune bullous diseases. British Journal of Dermatology. 191(2). 261–266. 3 indexed citations
5.
Noceti, Nicoletta, Alessandra Sciutti, Francesco Rea, et al.. (2023). Kinematic Primitives in Action Similarity Judgments: A Human-Centered Computational Model. IEEE Transactions on Cognitive and Developmental Systems. 15(4). 1981–1992.
6.
Pastore, Vito Paolo, Paola Proserpio, Laura Tassi, et al.. (2023). Automatic video analysis and classification of sleep‐related hypermotor seizures and disorders of arousal. Epilepsia. 64(6). 1653–1662. 12 indexed citations
7.
Zini, Luca, et al.. (2023). Knowledge distillation for efficient standard scanplane detection of fetal ultrasound. Medical & Biological Engineering & Computing. 62(1). 73–82. 1 indexed citations
8.
Pastore, Vito Paolo, et al.. (2022). A markerless pipeline to analyze spontaneous movements of preterm infants. Computer Methods and Programs in Biomedicine. 226. 107119–107119. 13 indexed citations
9.
Noceti, Nicoletta, Alessandra Sciutti, Francesco Rea, et al.. (2020). Action similarity judgment based on kinematic primitives. CINECA IRIS Institutial Research Information System (University of Genoa). 3 indexed citations
10.
Mari, Filippo De, et al.. (2018). The Radon transform intertwines wavelets and shearlets. Applied and Computational Harmonic Analysis. 47(3). 822–847. 6 indexed citations
11.
Fanello, Sean, Carlo Ciliberto, Matteo Santoro, et al.. (2013). iCub World: Friendly Robots Help Building Good Vision Data-Sets. PEARL (University of Plymouth). 700–705. 16 indexed citations
12.
Alanís, Alma Y., et al.. (2012). A wind speed neural model with particle swarm optimization Kalman learning. CINECA IRIS Institutial Research Information System (University of Genoa). 1–5. 5 indexed citations
13.
Mol, Christine De, et al.. (2008). A Sparsity-Enforcing Method for Learning Face Features. IEEE Transactions on Image Processing. 18(1). 188–201. 29 indexed citations
14.
Odone, Francesca, et al.. (2007). A trainable system for face detection in unconstrained environments. 407–412. 1 indexed citations
15.
Noceti, Nicoletta, et al.. (2007). Appearance-based 3D object recognition with time-invariant features. 467–474. 4 indexed citations
16.
Vito, Ernesto De, Lorenzo Rosasco, Andrea Caponnetto, Umberto De Giovannini, & Francesca Odone. (2005). Learning from Examples as an Inverse Problem. Journal of Machine Learning Research. 6(30). 883–904. 104 indexed citations
17.
Caponnetto, Andrea, Lorenzo Rosasco, Francesca Odone, & Alessandro Verri. (2005). Support vector algorithms as regularization networks.. The European Symposium on Artificial Neural Networks. 595–600. 1 indexed citations
18.
Isgrò, Francesco, et al.. (2005). Clustering for Surface Reconstruction. Max Planck Institute for Plasma Physics. 156–162. 1 indexed citations
19.
Rosasco, Lorenzo, Andrea Caponnetto, Ernesto De Vito, Francesca Odone, & Umberto De Giovannini. (2004). Learning, Regularization and Ill-Posed Inverse Problems. CINECA IRIS Institutial Research Information System (University of Genoa). 17. 1145–1152. 4 indexed citations
20.
Odone, Francesca, et al.. (2000). Robust motion segmentation for content-based video coding. 594–601. 8 indexed citations

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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