Davide Ceneda

524 citations
19 papers · 343 indexed · h-index 9

Davide Ceneda

17 papers receiving 337 citations

Peers

Davide Ceneda
Comparison fields: 5 of 63
  • Computer Vision and Pattern Recognition 262
  • Information Systems and Management 32
  • Signal Processing 49
  • Human-Computer Interaction 20
  • Computer Graphics and Computer-Aided Design 11
Replace Aoyu Wu with:
Aoyu Wu Hong Kong
Charles D. Stolper United States
Paolo Federico Austria
Hannah Kim United States
John Wenskovitch United States
Tera Marie Green Canada
Lars Grammel Canada
Kevin McDonald United Kingdom
Tim Lammarsch Austria
Fumeng Yang United States
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Citations per field
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Aoyu Wu · 1×
Citations per year

Countries citing papers authored by Davide Ceneda

Since Specialization
Citations

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

Fields of papers citing papers by Davide Ceneda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 18 scholars most cited alongside Davide Ceneda, 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 Davide Ceneda Line = papers co-authored together Davide Ceneda links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 20251
2 20251
3 20250
4 20242
5 20241
6 20241
7 20236
8 20234
9 202221
10 202213
11 202216
12 202110
13 202021
14 20206
15 20198
16 201951
17 201811
18 20163
19 2016167

About Davide Ceneda

Davide Ceneda is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Ecological Modeling, Information Systems and Management and Computational Theory and Mathematics, having authored 19 papers that have together received 343 indexed citations. Recurring topics across this work include Data Visualization and Analytics (15 papers), Video Analysis and Summarization (10 papers), Image and Video Quality Assessment (5 papers), Multimedia Communication and Technology (4 papers), Topological and Geometric Data Analysis (2 papers), Visual and Cognitive Learning Processes (1 paper), Personal Information Management and User Behavior (1 paper) and Gaze Tracking and Assistive Technology (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (262 citations), Information Systems and Management (32 citations), Signal Processing (49 citations), Human-Computer Interaction (20 citations) and Computer Graphics and Computer-Aided Design (11 citations). Davide Ceneda has collaborated with scholars based in Austria, Germany and Netherlands. Frequent co-authors include Silvia Miksch, Theresia Gschwandtner, Marc Streit, Christian Tominski, Thorsten May, Hans‐Jörg Schulz, Mennatallah El‐Assady, Fabian Sperrle, Markus Wagner and Wolfgang Aigner. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Computers & Graphics, Visual Informatics and Iris (Roma Tre University).

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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