Marko Švaco

481 citations
39 papers · 298 · h-index 10

Impact in

Papers in

Marko Švaco

36 papers receiving 281 citations

Peers

Marko Švaco
Comparison fields: 5 of 53
  • Control and Systems Engineering 98
  • Computer Vision and Pattern Recognition 78
  • Industrial and Manufacturing Engineering 36
  • Aerospace Engineering 72
  • Medical Laboratory Technology 3
Replace Filip Šuligoj with:
Filip Šuligoj Croatia
Bojan Jerbić Croatia
Marta Niccolini Italy
Kazutoshi Tanaka Japan
Libo Meng China
Zachary Ferguson United States
Pierluigi Rea Italy
Markus Giftthaler Switzerland
Seung-kook Yun United States
José de Gea Fernández Germany
Marko Švaco relative to Filip Šuligoj Croatia Filip Šuligoj's profile →
Citations per field
00.5×1.5×
Filip Šuligoj · 1×
Citations per year

Countries citing papers authored by Marko Švaco

Since Specialization
Citations

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

Fields of papers citing papers by Marko Švaco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Marko Švaco, 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 Marko Švaco Line = papers co-authored together Marko Švaco links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201464
2 201425
3 201718
4 201717
5 201517
6 201416
7 202114
8 201712
9 201111
10 201510
11 20218
12 20207
13 20187
14 20187
15 20177
16 20236
17 20196
18 20215
19
AUTONOMOUS ROBOT LEARNING MODEL BASED ON VISUAL INTERPRETATION OF SPATIAL STRUCTURES
20144
20 20224

About Marko Švaco

Marko Švaco is a scholar working on Control and Systems Engineering, Biomedical Engineering, Aerospace Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 39 papers that have together received 298 indexed citations. Recurring topics across this work include Soft Robotics and Applications (11 papers), Robotics and Sensor-Based Localization (9 papers), Robotic Path Planning Algorithms (6 papers), Robot Manipulation and Learning (5 papers), Robotic Mechanisms and Dynamics (4 papers), Scheduling and Optimization Algorithms (4 papers), Advanced Manufacturing and Logistics Optimization (3 papers) and Advanced Surface Polishing Techniques (3 papers). The work is most often cited by research in Control and Systems Engineering (98 citations), Computer Vision and Pattern Recognition (78 citations), Industrial and Manufacturing Engineering (36 citations), Aerospace Engineering (72 citations) and Medical Laboratory Technology (3 citations). Marko Švaco has collaborated with scholars based in Croatia. Frequent co-authors include Bojan Jerbić, Filip Šuligoj, Darko Chudy, Marina Raguž, Marijana Serdar, Darko Orešković, Matko Orsag, Zdenko Kovačić and Domagoj Damjanović. Their work appears in journals such as Tehnicki vjesnik - Technical Gazette, IEEE Access, Frontiers in Neurorobotics, Journal of Intelligent & Robotic Systems and International Journal of Simulation Modelling.

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.

Explore authors with similar magnitude of impact