Daniel Mendes

992 citations
51 papers · 676 · h-index 15

Impact in

Papers in

Daniel Mendes

46 papers receiving 659 citations

Peers

Daniel Mendes
Comparison fields: 5 of 70
  • Human-Computer Interaction 524
  • Computer Vision and Pattern Recognition 376
  • Computer Graphics and Computer-Aided Design 45
  • Cognitive Neuroscience 190
  • Geology 21
Replace Maurício Sousa with:
Maurício Sousa Portugal
Daniel Medeiros United Kingdom
Rajinder Singh Sodhi United States
David Lindlbauer United States
Yoshinari Kameda Japan
Julian Looser New Zealand
Difeng Yu Australia
Evan Suma Rosenberg United States
Christoph Anthes Germany
Kenrick Kin United States
Daniel Mendes relative to Maurício Sousa Portugal Maurício Sousa's profile →
Citations per field
00.5×1.5×2.2×
Maurício Sousa · 1×
Citations per year

Countries citing papers authored by Daniel Mendes

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Mendes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018107
2 201671
3 201769
4 201445
5 201728
6 201928
7 201727
8 201626
9 201825
10 201724
11 201719
12 201917
13 201616
14 202116
15 202215
16 202314
17 201113
18 201912
19 202012
20 202010

About Daniel Mendes

Daniel Mendes is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Mechanical Engineering and Control and Systems Engineering, having authored 51 papers that have together received 676 indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (27 papers), Interactive and Immersive Displays (24 papers), Augmented Reality Applications (18 papers), Tactile and Sensory Interactions (14 papers), Data Visualization and Analytics (7 papers), Teleoperation and Haptic Systems (3 papers), Human Motion and Animation (3 papers) and Hand Gesture Recognition Systems (3 papers). The work is most often cited by research in Human-Computer Interaction (524 citations), Computer Vision and Pattern Recognition (376 citations), Computer Graphics and Computer-Aided Design (45 citations), Cognitive Neuroscience (190 citations) and Geology (21 citations). Daniel Mendes has collaborated with scholars based in Portugal, Brazil and Italy. Frequent co-authors include Joaquim Jorge, Alfredo Ferreira, Maurício Sousa, Daniel Medeiros, Andrea Giachetti, Ariel Caputo, Alberto Raposo, Rafael Kuffner dos Anjos, Daniel Simões Lopes and Nuno Matela. Their work appears in journals such as Computers & Graphics, Computer Graphics Forum, Information Visualization, Proceedings of the ACM on Human-Computer Interaction and IEEE Transactions on Learning Technologies.

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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