Nenad Tomašev

11.5k citations
30 papers · 643 indexed · 1 hit paper · h-index 11
Topics
Face and Expression Recognition (8 papers)Advanced Image and Video Retrieval Techniques (5 papers)Image Retrieval and Classification Techniques (5 papers)

In The Last Decade

Nenad Tomašev

26 papers receiving 602 citations

Hit Papers

Advancing mathematics by guiding human intuition with AI2021202620222024202150100150200

Peers

Nenad Tomašev
Comparison fields: 5 of 124
  • Artificial Intelligence 377
  • Computer Vision and Pattern Recognition 126
  • Information Systems 74
  • Signal Processing 70
  • Computational Theory and Mathematics 47
Replace Petar Veličković with:
Petar Veličković United Kingdom
Shotaro Akaho Japan
David López-Paz Germany
Ludwig Schmidt United States
Saeid Gorgin Iran
Saif Al‐Kuwari Qatar
Po‐Ling Loh United States
Peter Kairouz United States
Zhiqiang Hu China
Eunho Yang South Korea
Nenad Tomašev relative to Petar Veličković United Kingdom Petar Veličković's profile →
Citations per field
00.5×10×20×30×39×
Petar Veličković · 1×
Citations per year

Countries citing papers authored by Nenad Tomašev

Since Specialization
Citations

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

Fields of papers citing papers by Nenad Tomašev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nenad Tomašev

This figure shows the co-authorship network connecting the top 25 collaborators of Nenad Tomašev. A scholar is included among the top collaborators of Nenad Tomašev based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nenad Tomašev. Nenad Tomašev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 3
4 0
5 2
6 36
7 6
8 10
9
Advancing mathematics by guiding human intuition with AIbreakdown →
243
10 3
11 1
12 18
13 1
14 0
15 81
16 2
17 31
18 17
19 18
20 28

About Nenad Tomašev

Nenad Tomašev is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 30 papers that have together received 643 indexed citations. Recurring topics across this work include Face and Expression Recognition (8 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Image Retrieval and Classification Techniques (5 papers). The work is most often cited by research in Health Informatics (26 citations), Artificial Intelligence (377 citations) and Signal Processing (70 citations). Nenad Tomašev has collaborated with scholars based in Slovenia, United Kingdom and United States. Frequent co-authors include Dunja Mladenić, Miloš Radovanović, Mirjana Ivanović, Demis Hassabis, Sam Blackwell, András Juhász, Petar Veličković, Lars Buesing, Marc Lackenby and Daniel Zheng. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

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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