Maria De Marsico

4.5k citations
137 papers · 2.2k indexed · h-index 25

Maria De Marsico

123 papers receiving 2.0k citations

Peers

Maria De Marsico
Comparison fields: 5 of 155
  • Signal Processing 732
  • Human-Computer Interaction 306
  • Computer Vision and Pattern Recognition 936
  • Computer Science Applications 214
  • Information Systems 565
Replace Genoveffa Tortora with:
Genoveffa Tortora Italy
Remco Chang United States
Giuseppe Carenini Canada
Marc Langheinrich Switzerland
Michael Terry Canada
Amy Karlson United States
Kaj Grønbæk Denmark
Hend S. Al‐Khalifa Saudi Arabia
Marco Roccetti Italy
Ted Selker United States
Maria De Marsico relative to Genoveffa Tortora Italy Genoveffa Tortora's profile →
Citations per field
00.5×1.5×2.4×
Genoveffa Tortora · 1×
Citations per year

Countries citing papers authored by Maria De Marsico

Since Specialization
Citations

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

Fields of papers citing papers by Maria De Marsico

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maria De Marsico. 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 Maria De Marsico. The network helps show where Maria De Marsico may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20240
2 20241
3 20240
4 202325
5 20224
6 202131
7 202045
8
GHItaly18: Game-human interaction in research
20180
9 201677
10 20160
11 20166
12 20169
13 201616
14 20159
15 201511
16 20156
17 20141
18 20131
19 201281
20 20129

About Maria De Marsico

Maria De Marsico is a scholar working on Human-Computer Interaction, Signal Processing and Computer Vision and Pattern Recognition, having authored 137 papers that have together received 2.2k indexed citations. Recurring topics across this work include Biometric Identification and Security (40 papers), Face recognition and analysis (29 papers), User Authentication and Security Systems (26 papers), Face and Expression Recognition (21 papers), Gait Recognition and Analysis (10 papers), Innovative Teaching and Learning Methods (9 papers), Hand Gesture Recognition Systems (8 papers) and Usability and User Interface Design (8 papers). The work is most often cited by research in Signal Processing (732 citations), Human-Computer Interaction (306 citations) and Computer Vision and Pattern Recognition (936 citations). Maria De Marsico has collaborated with scholars based in Italy, United States and Portugal. Frequent co-authors include Michele Nappi, Daniel Riccio, S. Levialdi, Teresa Roselli, Rosa Lanzilotti, Alessio Mecca, Harry Wechsler, Maria Francesca Costabile, Carmelo Ardito and Veronica Rossano. Their work appears in journals such as PLoS ONE, IEEE Transactions on Image Processing and IEEE Access.

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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