Anton Umek

1.2k total citations
66 papers, 824 citations indexed

About

Anton Umek is a scholar working on Biomedical Engineering, Orthopedics and Sports Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Anton Umek has authored 66 papers receiving a total of 824 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Biomedical Engineering, 30 papers in Orthopedics and Sports Medicine and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Anton Umek's work include Sports Performance and Training (30 papers), Muscle activation and electromyography studies (16 papers) and Sports Dynamics and Biomechanics (15 papers). Anton Umek is often cited by papers focused on Sports Performance and Training (30 papers), Muscle activation and electromyography studies (16 papers) and Sports Dynamics and Biomechanics (15 papers). Anton Umek collaborates with scholars based in Slovenia, China and Serbia. Anton Umek's co-authors include Anton Kos, Sašo Tomažič, Veljko Milutinović, Alessandro Santuz, Milivoj Dopsaj, Justin Keogh, Stefano Rossi, Yu Wei, Juri Taborri and Eline van der Kruk and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Applied Mechanics and Sensors.

In The Last Decade

Anton Umek

59 papers receiving 797 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Anton Umek Slovenia 17 328 253 148 100 84 66 824
Holger Harms Switzerland 12 326 1.0× 103 0.4× 134 0.9× 40 0.4× 75 0.9× 15 592
Bert-Jan van Beijnum Netherlands 19 529 1.6× 139 0.5× 218 1.5× 265 2.6× 105 1.3× 101 1.4k
Arnold Baca Austria 21 509 1.6× 693 2.7× 117 0.8× 38 0.4× 36 0.4× 125 1.4k
Sašo Tomažič Slovenia 19 252 0.8× 119 0.5× 203 1.4× 67 0.7× 255 3.0× 89 1.2k
Marc Bächlin Switzerland 12 497 1.5× 77 0.3× 299 2.0× 87 0.9× 104 1.2× 17 1.1k
Thomas Kautz Germany 10 199 0.6× 62 0.2× 169 1.1× 35 0.3× 52 0.6× 23 573
Georg Ogris Austria 11 198 0.6× 122 0.5× 331 2.2× 72 0.7× 39 0.5× 12 642
Dominik Schuldhaus Germany 10 283 0.9× 62 0.2× 263 1.8× 52 0.5× 28 0.3× 20 579
Alessandro Filippeschi Italy 14 310 0.9× 81 0.3× 131 0.9× 20 0.2× 118 1.4× 56 841

Countries citing papers authored by Anton Umek

Since Specialization
Citations

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

Fields of papers citing papers by Anton Umek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anton Umek

This figure shows the co-authorship network connecting the top 25 collaborators of Anton Umek. A scholar is included among the top collaborators of Anton Umek 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 Anton Umek. Anton Umek 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
1.
Tomažič, Sašo, et al.. (2024). Trends in real-time artificial intelligence methods in sports: a systematic review. Journal Of Big Data. 11(1). 7 indexed citations
2.
Jiao, Libin, et al.. (2023). Golf Guided Grad-CAM: attention visualization within golf swings via guided gradient-based class activation mapping. Multimedia Tools and Applications. 83(13). 38481–38503. 1 indexed citations
3.
Umek, Anton, et al.. (2023). Variability and the Correlation of Kinematic and Temporal Parameters in Different Modalities of the Reverse Punch Measured by Sensors. Applied Sciences. 13(18). 10348–10348. 1 indexed citations
4.
Umek, Anton, et al.. (2022). Review of Real-Time Biomechanical Feedback Systems in Sport and Rehabilitation. Sensors. 22(8). 3006–3006. 43 indexed citations
5.
Koropanovski, Nenad, et al.. (2022). Specific Test Design for the In-Depth Technique Analysis of Elite Karate Competitors with the Application of Kinematic Sensors. Applied Sciences. 12(16). 8048–8048. 4 indexed citations
6.
Marković, Stefan, Milivoj Dopsaj, Sašo Tomažič, et al.. (2021). Can IMU Provide an Accurate Vertical Jump Height Estimate?. Applied Sciences. 11(24). 12025–12025. 15 indexed citations
7.
Marković, Stefan, et al.. (2021). Use of IMU in Differential Analysis of the Reverse Punch Temporal Structure in Relation to the Achieved Maximal Hand Velocity. Sensors. 21(12). 4148–4148. 8 indexed citations
8.
Umek, Anton, et al.. (2021). A literature overview of real-time biofeedback applications in sport and rehabilitation. Repository of the University of Ljubljana (University of Ljubljana). 87–91. 1 indexed citations
9.
Marković, Stefan, Milivoj Dopsaj, Sašo Tomažič, & Anton Umek. (2020). Potential of IMU-Based Systems in Measuring Single Rapid Movement Variables in Females with Different Training Backgrounds and Specialization. Applied Bionics and Biomechanics. 2020. 1–7. 11 indexed citations
10.
Guo, Junqi, Lan Yang, Anton Umek, et al.. (2020). A Random Forest-Based Accuracy Prediction Model for Augmented Biofeedback in a Precision Shooting Training System. Sensors. 20(16). 4512–4512. 3 indexed citations
11.
Tomažič, Sašo, et al.. (2020). Cloud platform for biomechanical applications in sport and rehabilitation. International Conference on Information Society. 114–118. 2 indexed citations
12.
Marković, Stefan, et al.. (2020). The relationship of pistol movement measured by a kinematic sensor, shooting performance and handgrip strength. International Journal of Performance Analysis in Sport. 20(6). 1107–1119. 5 indexed citations
13.
Pustišek, Matevž, Anton Umek, & Andrej Kos. (2019). Approaching the Communication Constraints of Ethereum-Based Decentralized Applications. Sensors. 19(11). 2647–2647. 11 indexed citations
14.
Kos, Anton & Anton Umek. (2018). Wearable Sensor Devices for Prevention and Rehabilitation in Healthcare: Swimming Exercise With Real-Time Therapist Feedback. IEEE Internet of Things Journal. 6(2). 1331–1341. 72 indexed citations
15.
Kos, Anton, Veljko Milutinović, & Anton Umek. (2018). Challenges in wireless communication for connected sensors and wearable devices used in sport biofeedback applications. Future Generation Computer Systems. 92. 582–592. 60 indexed citations
16.
Umek, Anton, Yuan Zhang, Sašo Tomažič, & Anton Kos. (2017). Suitability of Strain Gage Sensors for Integration into Smart Sport Equipment: A Golf Club Example. Sensors. 17(4). 916–916. 24 indexed citations
17.
Kos, Anton & Anton Umek. (2017). Selection of sensor networks for biofeedback systems in healthcare and sports. International Conference on Information Society. 312–315. 1 indexed citations
18.
Jiao, Libin, Hao Wu, Rongfang Bie, Anton Kos, & Anton Umek. (2017). Contextual Spectrum Inpainting with Feature Learning and Context Losses. International Conference on Information Society. 293–298. 1 indexed citations
19.
Kos, Anton, Sašo Tomažič, & Anton Umek. (2016). Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications. Sensors. 16(3). 301–301. 37 indexed citations
20.
Kos, Anton, Sašo Tomažič, & Anton Umek. (2016). Evaluation of Smartphone Inertial Sensor Performance for Cross-Platform Mobile Applications. Sensors. 16(4). 477–477. 49 indexed citations

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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