Matteo Naccari

1.1k total citations
41 papers, 780 citations indexed

About

Matteo Naccari is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Electrical and Electronic Engineering. According to data from OpenAlex, Matteo Naccari has authored 41 papers receiving a total of 780 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Computer Vision and Pattern Recognition, 35 papers in Signal Processing and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Matteo Naccari's work include Video Coding and Compression Technologies (35 papers), Image and Video Quality Assessment (26 papers) and Advanced Image Processing Techniques (17 papers). Matteo Naccari is often cited by papers focused on Video Coding and Compression Technologies (35 papers), Image and Video Quality Assessment (26 papers) and Advanced Image Processing Techniques (17 papers). Matteo Naccari collaborates with scholars based in United Kingdom, Italy and Portugal. Matteo Naccari's co-authors include Marco Tagliasacchi, Stefano Tubaro, Fernando Pereira, F. Simone, Touradj Ebrahimi, Marta Mrak, Fréderic Dufaux, Davide Migliore, Matteo Matteucci and David S. Flynn and has published in prestigious journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia and IEEE Journal of Selected Topics in Signal Processing.

In The Last Decade

Matteo Naccari

41 papers receiving 751 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matteo Naccari United Kingdom 13 749 415 56 38 27 41 780
Tobias Hinz Germany 11 692 0.9× 600 1.4× 33 0.6× 20 0.5× 33 1.2× 23 733
Hadi Amirpour Austria 15 535 0.7× 362 0.9× 46 0.8× 66 1.7× 28 1.0× 96 637
Yaowu Xu United States 10 577 0.8× 423 1.0× 37 0.7× 23 0.6× 35 1.3× 53 629
Muhammad Shahid Sweden 12 345 0.5× 171 0.4× 70 1.3× 27 0.7× 20 0.7× 37 430
Karsten Mueller Germany 9 592 0.8× 390 0.9× 66 1.2× 27 0.7× 30 1.1× 23 632
Stéphane Coulombe Canada 12 382 0.5× 262 0.6× 44 0.8× 54 1.4× 46 1.7× 67 463
Chao‐Chung Cheng Taiwan 13 467 0.6× 232 0.6× 119 2.1× 19 0.5× 33 1.2× 25 500
V. Bhaskaran United States 12 448 0.6× 312 0.8× 43 0.8× 15 0.4× 28 1.0× 29 529
Anil Aksay Türkiye 10 296 0.4× 160 0.4× 59 1.1× 26 0.7× 27 1.0× 26 332

Countries citing papers authored by Matteo Naccari

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Naccari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Naccari

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Naccari. A scholar is included among the top collaborators of Matteo Naccari 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 Matteo Naccari. Matteo Naccari 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.
Agrafiotis, Dimitris K., et al.. (2017). Performance evaluation of reverse tone mapping operators for dynamic range expansion of SDR video content. Explore Bristol Research. 1–6. 5 indexed citations
2.
Naccari, Matteo, et al.. (2017). The Open-Source Turing Codec: Toward Fast, Flexible, and Parallel HEVC Encoding. SMPTE Motion Imaging Journal. 126(9). 1–8. 3 indexed citations
3.
Zupančić, I., Matteo Naccari, Marta Mrak, & Ebroul Izquierdo. (2016). Two-Pass Rate Control for Improved Quality of Experience in UHDTV Delivery. IEEE Journal of Selected Topics in Signal Processing. 11(1). 167–179. 22 indexed citations
4.
Zupančić, I., Matteo Naccari, Marta Mrak, & Ebroul Izquierdo. (2016). Studying rate control methods for UHDTV delivery using HEVC. 13. 47–50. 3 indexed citations
5.
Naccari, Matteo, et al.. (2015). Enabling Ultra High Definition Television services with the HEVC standard: The thira project. 39. 1–4. 1 indexed citations
6.
Naccari, Matteo, et al.. (2013). Improving inter prediction in HEVC with residual DPCM for lossless screen content coding. 361–364. 7 indexed citations
7.
Agrafiotis, Dimitris K., et al.. (2013). Visual masking phenomena with high dynamic range content. 2284–2288. 9 indexed citations
8.
Naccari, Matteo, et al.. (2013). High dynamic range video compression by intensity dependent spatial quantization in HEVC. 353–356. 9 indexed citations
9.
Naccari, Matteo & Fernando Pereira. (2012). Adaptive bilateral filter for improved in-loop filtering in the emerging high efficiency video coding standard. 397–400. 6 indexed citations
10.
Naccari, Matteo & Fernando Pereira. (2012). Quadratic modeling rate control in the emerging HEVC standard. 401–404. 10 indexed citations
11.
Naccari, Matteo, et al.. (2012). Spatial transform skip in the emerging High Efficiency Video Coding standard. 185–188. 8 indexed citations
12.
Naccari, Matteo & Fernando Pereira. (2011). Advanced H.264/AVC-Based Perceptual Video Coding: Architecture, Tools, and Assessment. IEEE Transactions on Circuits and Systems for Video Technology. 21(6). 766–782. 39 indexed citations
13.
Simone, F., Matteo Naccari, Marco Tagliasacchi, et al.. (2011). Subjective Quality Assessment of H.264/AVC Video Streaming with Packet Losses. EURASIP Journal on Image and Video Processing. 2011. 1–12. 31 indexed citations
14.
Naccari, Matteo, et al.. (2011). A new fast motion estimation and mode decision algorithm for H.264 depth maps encoding in free viewpoint TV. 7443. 1013–1016. 5 indexed citations
15.
Simone, F., Marco Tagliasacchi, Matteo Naccari, Stefano Tubaro, & Touradj Ebrahimi. (2010). A H.264/AVC video database for the evaluation of quality metrics. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2430–2433. 86 indexed citations
16.
Tagliasacchi, Marco, Giuseppe Valenzise, Matteo Naccari, & Stefano Tubaro. (2010). A reduced-reference structural similarity approximation for videos corrupted by channel errors. Multimedia Tools and Applications. 48(3). 471–492. 17 indexed citations
17.
Naccari, Matteo, Marco Tagliasacchi, & Stefano Tubaro. (2009). Subjective evaluation of a NO-reference video quality Monitoring algorithm for H.264/AVC video over a noisy channel. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 19. 4373–4376. 3 indexed citations
18.
Naccari, Matteo, Marco Tagliasacchi, Stefano Tubaro, et al.. (2008). Forward error protection for robust video streaming based on distributed video coding principles. CINECA IRIS Institutial Research Information System (University of Genoa). 747–752. 1 indexed citations
19.
Bernardini, Riccardo, Michele Fumagalli, Matteo Naccari, et al.. (2007). Error Concealment Using A Dvc Approach For Video Streaming Applications. CINECA IRIS Institutial Research Information System (University of Genoa). 668–672. 5 indexed citations
20.
Migliore, Davide, Matteo Matteucci, & Matteo Naccari. (2006). A revaluation of frame difference in fast and robust motion detection. 67 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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