Antonio Servetti

550 citations
43 papers · 318 · h-index 12

Impact in

Papers in

Antonio Servetti

38 papers receiving 297 citations

Peers

Antonio Servetti
Comparison fields: 5 of 54
  • Computer Vision and Pattern Recognition 170
  • Computer Networks and Communications 128
  • Signal Processing 50
  • Artificial Intelligence 94
  • Human-Computer Interaction 8
Replace Emad E. Abdallah with:
Emad E. Abdallah Jordan
Robert Zimmer United Kingdom
T. Gireesh Kumar India
Hua Yan China
Saroj Kumar Panigrahy India
Ignaz Rutter Germany
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Citations per year

Countries citing papers authored by Antonio Servetti

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Servetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Antonio Servetti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Antonio Servetti Line = papers co-authored together Antonio Servetti links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200252
2 200219
3
Adaptive Interactive Speech Transmission Over 802.11 Wireless LAN
200319
4 200418
5 200516
6 201215
7 201414
8 201913
9 202113
10 200512
11 201111
12 200411
13
Link-Level Unequal Error Detection for Speech Transmission over 802.11 Networks
200410
14 20229
15 20058
16 20227
17 20047
18 20166
19 20066
20 20206

About Antonio Servetti

Antonio Servetti is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Electrical and Electronic Engineering, Artificial Intelligence and Signal Processing, having authored 43 papers that have together received 318 indexed citations. Recurring topics across this work include Image and Video Quality Assessment (10 papers), Advanced Wireless Network Optimization (8 papers), Wireless Networks and Protocols (6 papers), Advanced Data Compression Techniques (5 papers), Network Traffic and Congestion Control (4 papers), Wireless Communication Security Techniques (4 papers), Network Security and Intrusion Detection (4 papers) and Caching and Content Delivery (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (170 citations), Computer Networks and Communications (128 citations), Signal Processing (50 citations), Artificial Intelligence (94 citations) and Human-Computer Interaction (8 citations). Antonio Servetti has collaborated with scholars based in Italy, Germany and Slovakia. Frequent co-authors include Juan Carlos De Martin, Enrico Masala, Matteo Petracca, Cristina Rottondi, Chris Chafe, Michela Meo, Marcus Barkowsky, Marina Bosi, Honghui Dong and Tania Cerquitelli. Their work appears in journals such as ACM Transactions on Multimedia Computing Communications and Applications, Journal of the Audio Engineering Society, Signal Processing Image Communication, IEEE Access and IEEE Transactions on Multimedia.

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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