Jean-Michel Pape

882 total citations
11 papers, 531 citations indexed

About

Jean-Michel Pape is a scholar working on Plant Science, Mechanical Engineering and Molecular Biology. According to data from OpenAlex, Jean-Michel Pape has authored 11 papers receiving a total of 531 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Plant Science, 5 papers in Mechanical Engineering and 2 papers in Molecular Biology. Recurrent topics in Jean-Michel Pape's work include Smart Agriculture and AI (5 papers), Tribology and Lubrication Engineering (4 papers) and Gear and Bearing Dynamics Analysis (3 papers). Jean-Michel Pape is often cited by papers focused on Smart Agriculture and AI (5 papers), Tribology and Lubrication Engineering (4 papers) and Gear and Bearing Dynamics Analysis (3 papers). Jean-Michel Pape collaborates with scholars based in Germany, Netherlands and Italy. Jean-Michel Pape's co-authors include Christian Klukas, Dijun Chen, Hanno Scharr, Massimo Minervini, Xi Yin, Imanol Luengo, Danijela Vukadinovic, Sotirios A. Tsaftaris, David Kramer and Xiaoming Liu and has published in prestigious journals such as PLANT PHYSIOLOGY, GigaScience and Machine Vision and Applications.

In The Last Decade

Jean-Michel Pape

11 papers receiving 505 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jean-Michel Pape Germany	7	420	206	72	69	62	11	531
Ashley Wheaton Australia	8	456 1.1×	196 1.0×	33 0.5×	82 1.2×	61 1.0×	9	617
Mikolaj Cieslak Canada	13	498 1.2×	103 0.5×	32 0.4×	39 0.6×	46 0.7×	29	671
Suk-Ju Hong South Korea	12	201 0.5×	112 0.5×	22 0.3×	58 0.8×	146 2.4×	33	516
Nicolas Virlet United Kingdom	11	622 1.5×	423 2.1×	89 1.2×	166 2.4×	136 2.2×	19	806
Chao Ruan China	13	353 0.8×	301 1.5×	25 0.3×	84 1.2×	193 3.1×	39	586
Tokihiro Fukatsu Japan	11	280 0.7×	125 0.6×	38 0.5×	69 1.0×	38 0.6×	44	503
Jordan Ubbens Canada	7	390 0.9×	189 0.9×	71 1.0×	56 0.8×	79 1.3×	9	499
Liangju Wang China	16	382 0.9×	257 1.2×	16 0.2×	74 1.1×	198 3.2×	45	621
Michael Pflanz Germany	14	458 1.1×	310 1.5×	17 0.2×	201 2.9×	212 3.4×	31	754
Yongjian Wang China	9	343 0.8×	165 0.8×	47 0.7×	133 1.9×	17 0.3×	22	449

Countries citing papers authored by Jean-Michel Pape

Since Specialization

Citations

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

Fields of papers citing papers by Jean-Michel Pape

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Michel Pape. 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 Jean-Michel Pape. The network helps show where Jean-Michel Pape may publish in the future.

Co-authorship network of co-authors of Jean-Michel Pape

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

All Works

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11 of 11 papers shown

1.

Chen, Dijun, Rongli Shi, Jean-Michel Pape, et al.. (2018). Predicting plant biomass accumulation from image-derived parameters. GigaScience. 7(2). 62 indexed citations

2.

Scharr, Hanno, Massimo Minervini, Andrew P. French, et al.. (2015). Leaf segmentation in plant phenotyping: a collation study. Machine Vision and Applications. 27(4). 585–606. 195 indexed citations

3.

Pape, Jean-Michel & Christian Klukas. (2015). Utilizing machine learning approaches to improve the prediction of leaf counts and individual leaf segmentation of rosette plant images. 3.1–3.12. 37 indexed citations

4.

Klukas, Christian, Dijun Chen, & Jean-Michel Pape. (2014). Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping . PLANT PHYSIOLOGY. 165(2). 506–518. 175 indexed citations

5.

Klukas, Christian, et al.. (2012). Analysis of high-throughput plant image data with the information system IAP. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 9(2). 16–18. 9 indexed citations

6.

Klukas, Christian, et al.. (2012). Analysis of high-throughput plant image data with the information system IAP. PubMed. 9(2). 191–191. 8 indexed citations

7.

Potente, H., et al.. (2006). Investigations into Kinematic Reversal in Non-isothermal Flows in Single-screw Machines. International Polymer Processing. 21(2). 116–120. 5 indexed citations

8.

Pape, Jean-Michel. (1969). Fundamental aspects of radial-face seals. Research Repository (Delft University of Technology). 6 indexed citations

9.

Pape, Jean-Michel. (1969). Fundamental research on a radial face seal. Tribology. 2(1). 77–77. 3 indexed citations

10.

Pape, Jean-Michel. (1968). Fundamental Research on a Radial Face Seal. A S L E Transactions. 11(4). 302–309. 27 indexed citations

11.

Pape, Jean-Michel, et al.. (1968). Viscoseal—Pressure Generation and Friction Loss under Turbulent Conditions. A S L E Transactions. 11(4). 310–320. 4 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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