Marco Dalai

921 citations
53 papers · 582 · h-index 9

Impact in

Papers in

Marco Dalai

51 papers receiving 568 citations

Peers

Marco Dalai
Comparison fields: 5 of 54
  • Computer Vision and Pattern Recognition 260
  • Signal Processing 111
  • Computer Networks and Communications 211
  • Computational Mathematics 4
  • Electrical and Electronic Engineering 385
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Victoria Kostina United States
Yasutada Oohama Japan
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Citations per field
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Citations per year

Countries citing papers authored by Marco Dalai

Since Specialization
Citations

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

Fields of papers citing papers by Marco Dalai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Marco Dalai, 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 Marco Dalai Line = papers co-authored together Marco Dalai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The DISCOVER codec: Architecture, Techniques and Evaluation
2007312
2
Lower Bounds to the Probability of Error for Classical and Classical-Quantum Channels
201634
3 200627
4 200721
5 201116
6 201715
7 200510
8 20219
9 20138
10 20148
11 20068
12 20067
13 20176
14 20126
15 20176
16 20216
17 20196
18 20205
19 20224
20 20204

About Marco Dalai

Marco Dalai is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 53 papers that have together received 582 indexed citations. Recurring topics across this work include Wireless Communication Security Techniques (14 papers), Coding theory and cryptography (11 papers), graph theory and CDMA systems (11 papers), Cooperative Communication and Network Coding (7 papers), Limits and Structures in Graph Theory (7 papers), Quantum Computing Algorithms and Architecture (5 papers), Music and Audio Processing (5 papers) and Speech and Audio Processing (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (260 citations), Signal Processing (111 citations), Computer Networks and Communications (211 citations), Computational Mathematics (4 citations) and Electrical and Electronic Engineering (385 citations). Marco Dalai has collaborated with scholars based in Italy, United States and Spain. Frequent co-authors include João Ascenso, Mourad Ouaret, Denis Kubasov, Sven Klomp, Riccardo Leonardi, Marco C. Campi, Fernando Pereira, Erik Weyer, Andreas Winter and Pierangelo Migliorati. Their work appears in journals such as IEEE Transactions on Information Theory, Discrete Applied Mathematics, IEEE Communications Letters, Multimedia Tools and Applications and International Journal of Circuit Theory 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.

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