Jasmin Kevrić

2.3k total citations · 2 hit papers
40 papers, 1.4k citations indexed

About

Jasmin Kevrić is a scholar working on Cognitive Neuroscience, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Jasmin Kevrić has authored 40 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cognitive Neuroscience, 9 papers in Signal Processing and 9 papers in Artificial Intelligence. Recurrent topics in Jasmin Kevrić's work include EEG and Brain-Computer Interfaces (11 papers), Blind Source Separation Techniques (7 papers) and ECG Monitoring and Analysis (4 papers). Jasmin Kevrić is often cited by papers focused on EEG and Brain-Computer Interfaces (11 papers), Blind Source Separation Techniques (7 papers) and ECG Monitoring and Analysis (4 papers). Jasmin Kevrić collaborates with scholars based in Bosnia and Herzegovina, Saudi Arabia and Australia. Jasmin Kevrić's co-authors include Abdülhamit Subaşı, Emina Aličković, Samed Jukić, M. Abdullah Canbaz, Zerina Mašetić, Muzafer Saračević, Leandro Pecchia, Almir Badnjević, Lejla Gurbeta Pokvić and Dženana Đonko and has published in prestigious journals such as Neural Computing and Applications, Measurement and Forensic Science International.

In The Last Decade

Jasmin Kevrić

36 papers receiving 1.3k citations

Hit Papers

Performance evaluation of empirical mode decomposition, d... 2016 2026 2019 2022 2017 2016 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction
    2017 313 citations Emina Aličković, Jasmin Kevrić et al. Biomedical Signal Processing and Control profile →
  2. Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system
    2016 313 citations Jasmin Kevrić, Abdülhamit Subaşı Biomedical Signal Processing and Control profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jasmin Kevrić Bosnia and Herzegovina 14 824 528 294 199 176 40 1.4k
Cosimo Ieracitano Italy 19 873 1.1× 212 0.4× 440 1.5× 210 1.1× 141 0.8× 42 1.7k
Enas Abdulhay Jordan 22 772 0.9× 242 0.5× 316 1.1× 284 1.4× 123 0.7× 49 2.1k
Muhammad Tariq Sadiq China 28 1.2k 1.5× 358 0.7× 445 1.5× 333 1.7× 270 1.5× 67 2.3k
Shufang Li China 20 502 0.6× 362 0.7× 290 1.0× 114 0.6× 74 0.4× 108 2.1k
Syed Umar Amin Saudi Arabia 24 1.2k 1.5× 360 0.7× 585 2.0× 191 1.0× 451 2.6× 47 2.8k
Smith K. Khare India 26 1.2k 1.4× 304 0.6× 263 0.9× 461 2.3× 82 0.5× 43 1.8k
Ergun Erçelebi Türkiye 16 410 0.5× 311 0.6× 251 0.9× 174 0.9× 59 0.3× 69 1.4k
Umut Orhan Türkiye 15 836 1.0× 323 0.6× 177 0.6× 131 0.7× 200 1.1× 50 1.1k
Gaowei Xu China 15 327 0.4× 148 0.3× 242 0.8× 70 0.4× 81 0.5× 24 1.3k
Katharina Eggensperger Germany 9 2.0k 2.4× 437 0.8× 750 2.6× 240 1.2× 620 3.5× 12 3.0k

Countries citing papers authored by Jasmin Kevrić

Since Specialization
Citations

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

Fields of papers citing papers by Jasmin Kevrić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jasmin Kevrić

This figure shows the co-authorship network connecting the top 25 collaborators of Jasmin Kevrić. A scholar is included among the top collaborators of Jasmin Kevrić 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 Jasmin Kevrić. Jasmin Kevrić 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.
2.
Ademović, Naida, Jasmin Kevrić, & Zlatan Akšamija. (2023). Advanced Technologies, Systems, and Applications VIII. Lecture notes in networks and systems. 1 indexed citations
3.
4.
Sarić, Rijad, et al.. (2022). Dental age assessment based on CBCT images using machine learning algorithms. Forensic Science International. 334. 111245–111245. 16 indexed citations
5.
Kevrić, Jasmin, et al.. (2022). Human Activity Recognition Using Ambient Sensor Data. IFAC-PapersOnLine. 55(4). 97–102. 1 indexed citations
6.
Kevrić, Jasmin, et al.. (2021). Deep Learning-Based Studies on Pediatric Brain Tumors Imaging: Narrative Review of Techniques and Challenges. Brain Sciences. 11(6). 716–716. 19 indexed citations
7.
Kevrić, Jasmin, et al.. (2021). Feature selection using cloud-based parallel genetic algorithm for intrusion detection data classification. Neural Computing and Applications. 33(18). 11861–11873. 19 indexed citations
8.
Kevrić, Jasmin, et al.. (2020). Lung cancer typology classification based on biochemical markers using machine learning techniques. 292–297. 5 indexed citations
9.
Mašetić, Zerina, et al.. (2019). Car Price Prediction using Machine Learning Techniques. TEM Journal. 113–118. 68 indexed citations
10.
11.
Badnjević, Almir, et al.. (2019). Evidence-based clinical engineering: Machine learning algorithms for prediction of defibrillator performance. Biomedical Signal Processing and Control. 54. 101629–101629. 54 indexed citations
12.
13.
Jukić, Samed, et al.. (2018). Majority Vote of Ensemble Machine Learning Methods for Real-Time Epilepsy Prediction Applied on EEG Pediatric Data. TEM Journal. 313–318. 6 indexed citations
14.
Kevrić, Jasmin, et al.. (2018). New algorithm for distribution system reconstruction planning based on fuzzy inference and multicriteria decision making. Engineering review. 38(2). 232–241. 2 indexed citations
15.
Subaşı, Abdülhamit, Jasmin Kevrić, & M. Abdullah Canbaz. (2017). Epileptic seizure detection using hybrid machine learning methods. Neural Computing and Applications. 31(1). 317–325. 208 indexed citations
16.
Aličković, Emina, Jasmin Kevrić, & Abdülhamit Subaşı. (2017). Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction. Biomedical Signal Processing and Control. 39. 94–102. 313 indexed citations breakdown →
17.
Kevrić, Jasmin & Abdülhamit Subaşı. (2016). Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system. Biomedical Signal Processing and Control. 31. 398–406. 313 indexed citations breakdown →
18.
Jukić, Samed, et al.. (2015). COMPARISON OF MACHINE LEARNING TECHNIQUES IN SPAM E-MAIL CLASSIFICATION. 4(1). 1 indexed citations
19.
Kevrić, Jasmin & Abdülhamit Subaşı. (2015). The Impact of Mspca Signal De-Noising In Real-Time Wireless Brain Computer Interface System. 4(1). 11 indexed citations
20.
Kevrić, Jasmin & Abdülhamit Subaşı. (2014). The Effect of Multiscale PCA De-noising in Epileptic Seizure Detection. Journal of Medical Systems. 38(10). 131–131. 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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