E. S. Gelsema

1.3k total citations
71 papers, 898 citations indexed

About

E. S. Gelsema is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Surfaces, Coatings and Films. According to data from OpenAlex, E. S. Gelsema has authored 71 papers receiving a total of 898 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 10 papers in Surfaces, Coatings and Films. Recurrent topics in E. S. Gelsema's work include Digital Imaging for Blood Diseases (14 papers), AI in cancer detection (11 papers) and Electron and X-Ray Spectroscopy Techniques (10 papers). E. S. Gelsema is often cited by papers focused on Digital Imaging for Blood Diseases (14 papers), AI in cancer detection (11 papers) and Electron and X-Ray Spectroscopy Techniques (10 papers). E. S. Gelsema collaborates with scholars based in Netherlands, United States and Switzerland. E. S. Gelsema's co-authors include Jifke F. Veenland, Chris J. Snijders, Kourosh Kiani, Laveen N. Kanal, Daniel Q. Naiman, Arnaud Beckers, J. L. Grashuis, W.C. de Bruijn, Guinevere F. Eden and Thomas Link and has published in prestigious journals such as Technometrics, Hypertension and Pattern Recognition.

In The Last Decade

E. S. Gelsema

67 papers receiving 839 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
E. S. Gelsema Netherlands	16	214	196	114	91	71	71	898
Stelios C. Orphanoudakis Greece	19	509 2.4×	180 0.9×	86 0.8×	78 0.9×	355 5.0×	102	1.3k
Ranjan Maitra United States	20	111 0.5×	472 2.4×	91 0.8×	78 0.9×	163 2.3×	73	1.3k
Amit Chakraborty India	16	300 1.4×	87 0.4×	60 0.5×	34 0.4×	106 1.5×	65	956
Peter Santago United States	15	211 1.0×	88 0.4×	77 0.7×	64 0.7×	238 3.4×	35	773
Inga Strümke Norway	9	102 0.5×	271 1.4×	85 0.7×	45 0.5×	168 2.4×	35	892
William J. Ohley United States	14	221 1.0×	135 0.7×	194 1.7×	109 1.2×	179 2.5×	42	990
Pablo G. Tahoces Spain	17	456 2.1×	487 2.5×	110 1.0×	110 1.2×	370 5.2×	55	1.1k
Zhonghai Wang United States	19	112 0.5×	315 1.6×	77 0.7×	68 0.7×	57 0.8×	140	1.2k
Huijun Hu China	22	223 1.0×	129 0.7×	88 0.8×	423 4.6×	121 1.7×	128	1.6k
Donghan M. Yang United States	16	118 0.6×	437 2.2×	85 0.7×	142 1.6×	517 7.3×	47	1.1k

Countries citing papers authored by E. S. Gelsema

Since Specialization

Citations

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

Fields of papers citing papers by E. S. Gelsema

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. S. Gelsema. 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 E. S. Gelsema. The network helps show where E. S. Gelsema may publish in the future.

Co-authorship network of co-authors of E. S. Gelsema

This figure shows the co-authorship network connecting the top 25 collaborators of E. S. Gelsema. A scholar is included among the top collaborators of E. S. Gelsema 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 E. S. Gelsema. E. S. Gelsema 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

Tulen, J.H.M., et al.. (2000). Assessment of body position to quantify its effect on nocturnal blood pressure under ambulatory conditions. Journal of Hypertension. 18(12). 1737–1743. 14 indexed citations

Kiani, Kourosh, Chris J. Snijders, & E. S. Gelsema. (1998). Recognition of daily life motor activity classes using an artificial neural network. Archives of Physical Medicine and Rehabilitation. 79(2). 147–154. 33 indexed citations

Veenland, Jifke F., J. L. Grashuis, & E. S. Gelsema. (1998). Texture analysis in radiographs: The influence of modulation transfer function and noise on the discriminative ability of texture features. Medical Physics. 25(6). 922–936. 28 indexed citations

Lindemans, Jan, et al.. (1997). A computer program for constructing multivariate reference models. Computer Methods and Programs in Biomedicine. 53(3). 191–200. 6 indexed citations

Veenland, Jifke F., et al.. (1997). Unraveling the Role of Structure and Density in Determining Vertebral Bone Strength. Calcified Tissue International. 61(6). 474–479. 57 indexed citations

Bonke, B., et al.. (1997). Evaluation of Techniques for the Presentation of Laboratory Data. I: Time Needed for Interpretation. Methods of Information in Medicine. 36(1). 11–16. 5 indexed citations

Gelsema, E. S.. (1997). Analysis of Metacarpophalangeal Profiles by Pattern Recognition Techniques. Investigative Radiology. 32(2). 73–82. 2 indexed citations

Veenland, Jifke F., et al.. (1996). Estimation of fractal dimension in radiographs. Medical Physics. 23(4). 585–594. 64 indexed citations

Beckers, Arnaud, et al.. (1996). Quantitative electron spectroscopic imaging in bio‐medicine: evaluation and application. Journal of Microscopy. 183(1). 78–88. 12 indexed citations

10.

Veenland, Jifke F., et al.. (1996). Comparison of two fractal dimension estimation methods in predicting fracture risk in vertebrae. Osteoporosis International. 6(S1). 146–146. 1 indexed citations

11.

Gelsema, E. S. & Laveen N. Kanal. (1994). Pattern Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems: Proceedings of an International Workshop Held in Vlieland, the Netherlands, 1-3 June 1994. Elsevier eBooks. 1 indexed citations

12.

Gelsema, E. S., et al.. (1994). A new representation of acid-base disturbances. International Journal of Bio-Medical Computing. 36(3). 209–221. 1 indexed citations

13.

Beckers, Arnaud, et al.. (1992). Correspondence Analysis for Quantification in Electron Energy Loss Spectroscopy and Imaging. Methods of Information in Medicine. 31(1). 29–35. 2 indexed citations

14.

Gelsema, E. S., et al.. (1991). Quantitative analysis of electron energy‐loss spectra from ultrathin‐sectioned biological material. Journal of Microscopy. 162(1). 43–54. 8 indexed citations

15.

Gelsema, E. S., et al.. (1991). Quantitative analysis of electron energy‐loss spectra from ultrathin‐sectioned biological material. Journal of Microscopy. 162(1). 23–42. 11 indexed citations

16.

Bins, M., et al.. (1989). Neutrophil granulation stained with May Gruenwald Giemsa or pure Azure B-eosin Y quantified by image analysis. Annals of Hematology. 58(2). 79–82. 2 indexed citations

17.

Gelsema, E. S., et al.. (1988). Application of the method of multiple thresholding to white blood cell classification. Computers in Biology and Medicine. 18(2). 65–74. 5 indexed citations

18.

Gelsema, E. S., et al.. (1987). Automated white blood cell classification revisited. Medical Informatics. 12(1). 23–31. 2 indexed citations

19.

Gelsema, E. S. & Laveen N. Kanal. (1986). Pattern recognition in practice II : proceedings of an international workshop held in Amsterdam, June 19-21, 1985. North-Holland eBooks.

20.

Gelsema, E. S. & Guinevere F. Eden. (1980). Mapping algorithms in ispahan. Pattern Recognition. 12(3). 127–136. 19 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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