Klemen Grm
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Artificial Intelligence
- Radiology, Nuclear Medicine and Imaging
- Cognitive Neuroscience
- Co-authors
- Vitomir ŠtrucHazım Kemal EkenelSimon DobrišekPatrick J. FlynnDacheng TaoPeter PeerChangxing DingYu Zhu
- Topics
- Face recognition and analysis (6 papers)Biometric Identification and Security (5 papers)Generative Adversarial Networks and Image Synthesis (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionSignal ProcessingBusiness and International Management
- Journals
- IEEE Transactions on Dependable and Secure ComputingIET BiometricsIstanbul Technical University Academic Open Archive (Istanbul Technical University)
- Partner nations
- SloveniaTürkiyeUnited States
In The Last Decade
Klemen Grm
7 papers receiving 174 citations
Peers
Comparison fields: 5 of 60
- Computer Vision and Pattern Recognition 135
- Signal Processing 64
- Artificial Intelligence 31
- Radiology, Nuclear Medicine and Imaging 14
- Cognitive Neuroscience 8
Countries citing papers authored by Klemen Grm
This map shows the geographic impact of Klemen Grm'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 Klemen Grm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Klemen Grm more than expected).
Fields of papers citing papers by Klemen Grm
This network shows the impact of papers produced by Klemen Grm. 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 Klemen Grm. The network helps show where Klemen Grm may publish in the future.
Co-authorship network of co-authors of Klemen Grm
This figure shows the co-authorship network connecting the top 25 collaborators of Klemen Grm. A scholar is included among the top collaborators of Klemen Grm 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 Klemen Grm. Klemen Grm is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | Analysis of Race and Gender Bias in Deep Age Estimation Models | 1 |
| 4 | 12 | |
| 5 | 146 | |
| 6 | 12 | |
| 7 | 5 |
About Klemen Grm
Klemen Grm is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Health, having authored 7 papers that have together received 181 indexed citations. Recurring topics across this work include Face recognition and analysis (6 papers), Biometric Identification and Security (5 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (135 citations), Signal Processing (64 citations) and Business and International Management (2 citations). Klemen Grm has collaborated with scholars based in Slovenia, Türkiye and United States. Frequent co-authors include Vitomir Štruc, Hazım Kemal Ekenel, Simon Dobrišek, Patrick J. Flynn, Dacheng Tao, Peter Peer, Changxing Ding, Yu Zhu, Peter Rot and Guodong Guo. Their work appears in journals such as IEEE Transactions on Dependable and Secure Computing, IET Biometrics and Istanbul Technical University Academic Open Archive (Istanbul Technical 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.