Iuri Frosio

4.4k total citations · 1 hit paper
53 papers, 2.5k citations indexed

About

Iuri Frosio is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Iuri Frosio has authored 53 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Iuri Frosio's work include Image and Signal Denoising Methods (12 papers), Medical Imaging Techniques and Applications (9 papers) and Medical Image Segmentation Techniques (7 papers). Iuri Frosio is often cited by papers focused on Image and Signal Denoising Methods (12 papers), Medical Imaging Techniques and Applications (9 papers) and Medical Image Segmentation Techniques (7 papers). Iuri Frosio collaborates with scholars based in Italy, United States and United Kingdom. Iuri Frosio's co-authors include Jan Kautz, Orazio Gallo, Hang Zhao, N. Alberto Borghese, Federico Pedersini, Federica Sibella, Federico Schena, Shalini Gupta, D. Sudheer Reddy and Jason Clemons and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging and Pattern Recognition.

In The Last Decade

Iuri Frosio

50 papers receiving 2.4k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Loss Functions for Image Restoration With Neural Networks

2016 1.7k citations Hang Zhao, Orazio Gallo et al. IEEE Transactions on Computational Imaging profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Iuri Frosio Italy	14	1.5k	642	315	300	276	53	2.5k
Anup Basu Canada	28	2.2k 1.5×	706 1.1×	265 0.8×	259 0.9×	407 1.5×	264	3.4k
Alain Horé Canada	8	2.0k 1.4×	746 1.2×	299 0.9×	297 1.0×	269 1.0×	16	2.8k
Richard J. Radke United States	27	2.0k 1.3×	807 1.3×	510 1.6×	135 0.5×	538 1.9×	102	3.5k
Hanseok Ko South Korea	24	1.2k 0.8×	476 0.7×	196 0.6×	192 0.6×	736 2.7×	305	2.6k
Lu Fang China	26	1.6k 1.1×	358 0.6×	230 0.7×	197 0.7×	309 1.1×	188	2.4k
Rui Huang China	23	2.0k 1.3×	509 0.8×	275 0.9×	322 1.1×	390 1.4×	111	2.8k
Yee‐Hong Yang Canada	36	2.9k 2.0×	618 1.0×	193 0.6×	188 0.6×	310 1.1×	162	3.7k
Tingfa Xu China	22	1.8k 1.2×	498 0.8×	179 0.6×	225 0.8×	294 1.1×	154	2.4k
Qingmin Liao China	30	2.9k 2.0×	1.1k 1.8×	258 0.8×	209 0.7×	553 2.0×	282	4.1k
A. Ardeshir Goshtasby United States	23	1.9k 1.3×	811 1.3×	319 1.0×	318 1.1×	255 0.9×	50	2.8k

Countries citing papers authored by Iuri Frosio

Since Specialization

Citations

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

Fields of papers citing papers by Iuri Frosio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iuri Frosio

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Spjut, Josef, et al.. (2025). Modeling visually-guided aim-and-shoot behavior in first-person shooters. International Journal of Human-Computer Studies. 199. 103503–103503.

Frosio, Iuri, Chen Tessler, Gilbert Bernstein, et al.. (2024). Learning to Move Like Professional Counter‐Strike Players. Computer Graphics Forum. 43(8). 1 indexed citations

Clemons, Jason, et al.. (2023). Augmenting Legacy Networks for Flexible Inference. 1–8. 1 indexed citations

Frosio, Iuri, et al.. (2020). Accelerating Reinforcement Learning Through GPU Atari Emulation. Neural Information Processing Systems. 33. 19773–19782. 1 indexed citations

Mahmoud, Abdulrahman, et al.. (2020). PyTorchFI: A Runtime Perturbation Tool for DNNs. 25–31. 77 indexed citations

Frosio, Iuri, et al.. (2019). GPU-Accelerated Atari Emulation for Reinforcement Learning. arXiv (Cornell University). 1 indexed citations

Frosio, Iuri & Jan Kautz. (2018). Statistical Nearest Neighbors for Image Denoising. IEEE Transactions on Image Processing. 28(2). 723–738. 31 indexed citations

Clemons, Jason, et al.. (2016). A patch memory system for image processing and computer vision. International Symposium on Microarchitecture. 1–13. 10 indexed citations

Zhao, Hang, Orazio Gallo, Iuri Frosio, & Jan Kautz. (2016). Loss Functions for Image Restoration With Neural Networks. IEEE Transactions on Computational Imaging. 3(1). 47–57. 1662 indexed citations breakdown →

10.

Frosio, Iuri, et al.. (2011). Optimized acquisition geometry for X-ray inspection. 53. 1–6. 6 indexed citations

11.

Frosio, Iuri & N. Alberto Borghese. (2009). Compression and smart coding of offset and gain maps for intraoral digital x‐ray sensors. Medical Physics. 36(2). 464–479. 4 indexed citations

12.

Frosio, Iuri, Silvio Abati, & N. Alberto Borghese. (2008). An expectation maximization approach to impulsive noise removal in digital radiography. International Journal of Computer Assisted Radiology and Surgery. 3(1-2). 91–96. 1 indexed citations

13.

Frosio, Iuri, et al.. (2007). A new and reliable Poisson noise estimator for radiographic images. 725–730. 4 indexed citations

14.

Frosio, Iuri, et al.. (2007). A new and reliable Poisson noise estimator for radiographic images. 725–730. 4 indexed citations

15.

Sibella, Federica, Iuri Frosio, Federico Schena, & N. Alberto Borghese. (2007). 3D analysis of the body center of mass in rock climbing. Human Movement Science. 26(6). 841–852. 66 indexed citations

16.

Frosio, Iuri & N. Alberto Borghese. (2007). Real-time accurate circle fitting with occlusions. Pattern Recognition. 41(3). 1041–1055. 43 indexed citations

17.

Sibella, Federica, Iuri Frosio, N. Alberto Borghese, & Federico Schena. (2007). 3D ANALYSIS OF THE BODY CENTRE OF MASS IN ROCK CLIMBING. 1(1). 841–852. 8 indexed citations

18.

Frosio, Iuri & N. Alberto Borghese. (2006). Real Time Enhancement of Cephalometric Radiographies. 972–975. 10 indexed citations

19.

Frosio, Iuri & N. Alberto Borghese. (2006). A new real time filter for local exposure correction in panoramic radiographs. Medical Physics. 33(9). 3478–3488. 1 indexed citations

20.

Ferrari, Stefano, Iuri Frosio, Vincenzo Piuri, & N. Alberto Borghese. (2004). Enhanced vector quantization for data reduction and filtering. 470–477. 1 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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