Thomas Fevens

1.6k total citations
69 papers, 901 citations indexed

About

Thomas Fevens is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Thomas Fevens has authored 69 papers receiving a total of 901 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computer Vision and Pattern Recognition, 23 papers in Computer Networks and Communications and 19 papers in Artificial Intelligence. Recurrent topics in Thomas Fevens's work include Mobile Ad Hoc Networks (18 papers), Opportunistic and Delay-Tolerant Networks (13 papers) and AI in cancer detection (12 papers). Thomas Fevens is often cited by papers focused on Mobile Ad Hoc Networks (18 papers), Opportunistic and Delay-Tolerant Networks (13 papers) and AI in cancer detection (12 papers). Thomas Fevens collaborates with scholars based in Canada, China and Poland. Thomas Fevens's co-authors include Adam Krzyżak, Alaa E. Abdallah, Paweł Filipczuk, Josef Opatrný, Roman Monczak, Shuo Li, Łukasz Jeleń, Jaroslav Opatrny, Li Song and Chao Jin and has published in prestigious journals such as The American Journal of Sports Medicine, IEEE Transactions on Medical Imaging and Sensors.

In The Last Decade

Thomas Fevens

63 papers receiving 857 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas Fevens Canada	17	372	325	283	197	144	69	901
H.S. Bhadauria India	18	525 1.4×	351 1.1×	159 0.6×	226 1.1×	85 0.6×	62	920
Wei Zou China	13	195 0.5×	463 1.4×	178 0.6×	53 0.3×	94 0.7×	43	1.0k
Saeed Sadri Iran	16	252 0.7×	187 0.6×	107 0.4×	239 1.2×	250 1.7×	53	870
Mukesh D. Patil India	12	294 0.8×	99 0.3×	34 0.1×	60 0.3×	193 1.3×	60	721
Anne C. Elster Norway	10	192 0.5×	96 0.3×	112 0.4×	87 0.4×	39 0.3×	50	501
Shanlin Sun China	10	228 0.6×	172 0.5×	180 0.6×	170 0.9×	92 0.6×	47	736
Ghada M. El‐Banby Egypt	20	577 1.6×	219 0.7×	84 0.3×	151 0.8×	76 0.5×	84	1.1k
Priyanka Kokil India	16	206 0.6×	131 0.4×	101 0.4×	233 1.2×	90 0.6×	91	931
Jie Yao China	14	152 0.4×	188 0.6×	9 0.0×	121 0.6×	112 0.8×	39	655
Chris G. Willcocks United Kingdom	9	319 0.9×	232 0.7×	39 0.1×	153 0.8×	14 0.1×	20	627

Countries citing papers authored by Thomas Fevens

Since Specialization

Citations

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

Fields of papers citing papers by Thomas Fevens

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Fevens

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Fevens. A scholar is included among the top collaborators of Thomas Fevens 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 Thomas Fevens. Thomas Fevens is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Reidler, Paul, et al.. (2025). MRI as a viable alternative to CT for 3D surgical planning of cavitary bone tumors. Magnetic Resonance Imaging. 119. 110369–110369.

Corban, Jason, Louis‐Nicolas Veilleux, Stephane G. Bergeron, et al.. (2024). Comparing a Portable Motion Analysis System against the Gold Standard for Potential Anterior Cruciate Ligament Injury Prevention and Screening. Sensors. 24(6). 1970–1970. 6 indexed citations

Corban, Jason, et al.. (2024). Comparing the Drop Vertical Jump Tracking Performance of the Azure Kinect to the Kinect V2. Sensors. 24(12). 3814–3814. 2 indexed citations

Reidler, Paul, Bastian O. Sabel, Jakob Dexl, et al.. (2024). Computer vision-based guidance tool for correct radiographic hand positioning. 593. 39–39. 1 indexed citations

Fevens, Thomas, et al.. (2024). Comparing novel smartphone pose estimation frameworks with the Kinect V2 for knee tracking during athletic stress tests. International Journal of Computer Assisted Radiology and Surgery. 19(7). 1321–1328. 1 indexed citations

Fevens, Thomas, et al.. (2024). Brain MRI Tumour Localization and Segmentation Through Deep Learning. 782–786.

Corban, Jason, et al.. (2023). Using an Affordable Motion Capture System to Evaluate the Prognostic Value of Drop Vertical Jump Parameters for Noncontact ACL Injury. The American Journal of Sports Medicine. 51(4). 1059–1066. 9 indexed citations

Fevens, Thomas, et al.. (2022). A Novel Approach for Selecting Effective Threshold Values in Ternary State Estimation Using Particle Swarm Optimization. Applied Sciences. 12(21). 10693–10693. 1 indexed citations

Fevens, Thomas, et al.. (2021). Uncertainty-Aware Policy Sampling and Mixing for Safe Interactive Imitation Learning. 72–78. 2 indexed citations

10.

Jeleń, Łukasz, Adam Krzyżak, Thomas Fevens, & Michał Jeleń. (2016). Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies. Computers in Biology and Medicine. 79. 80–91. 21 indexed citations

11.

Filipczuk, Paweł, Thomas Fevens, Adam Krzyżak, & Andrzej Obuchowicz. (2012). GLCM AND GLRLM BASED TEXTURE FEATURES FOR COMPUTER-AIDED BREAST CANCER DIAGNOSIS. Journal of Medical Informatics & Technologies. 19. 11 indexed citations

12.

Krzyżak, Adam, et al.. (2011). APPLICATION OF PATTERN RECOGNITION TECHNIQUES FOR THE ANALYSIS OF THIN BLOOD SMEAR IMAGES. Journal of Medical Informatics & Technologies. 18. 8 indexed citations

13.

Abdallah, Alaa E., Thomas Fevens, & Jaroslav Opatrny. (2010). 3D Local Algorithm for Dominating Sets of Unit Disk Graphs. Ad Hoc & Sensor Wireless Networks. 19. 21–38. 1 indexed citations

14.

Abdallah, Alaa E., Thomas Fevens, Josef Opatrný, & Ivan Stojmenović. (2009). Power-aware semi-beaconless 3D georouting algorithms using adjustable transmission ranges for wireless ad hoc and sensor networks. Ad Hoc Networks. 8(1). 15–29. 21 indexed citations

15.

Fevens, Thomas, et al.. (2007). A Class of Orientation-Invariant Yao-type Subgraphs of a Unit Disk Graph.. BMC Cancer. 7. 16–16. 1 indexed citations

16.

Li, Shuo, et al.. (2007). Semi-automatic computer aided lesion detection in dental X-rays using variational level set. Pattern Recognition. 40(10). 2861–2873. 52 indexed citations

17.

Li, Shuo, et al.. (2006). An automatic variational level set segmentation framework for computer aided dental X-rays analysis in clinical environments. Computerized Medical Imaging and Graphics. 30(2). 65–74. 41 indexed citations

18.

Li, Shuo, et al.. (2005). Toward Automatic Computer Aided Dental X-ray Analysis Using Level Set Method. Lecture notes in computer science. 8(Pt 1). 670–678. 10 indexed citations

19.

Aloupis, Greg, et al.. (2003). Computing the Similarity of two Melodies.. Tokyo Tech Research Repository (Tokyo Institute of Technology). 81–84. 2 indexed citations

20.

Fevens, Thomas, Henk Meijer, & David Rappaport. (2001). Minimum convex partition of a constrained point set. Discrete Applied Mathematics. 109(1-2). 95–107. 12 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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