Thomas C.W. Landgrebe

763 total citations
19 papers, 532 citations indexed

About

Thomas C.W. Landgrebe is a scholar working on Artificial Intelligence, Geophysics and Geochemistry and Petrology. According to data from OpenAlex, Thomas C.W. Landgrebe has authored 19 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 7 papers in Geophysics and 6 papers in Geochemistry and Petrology. Recurrent topics in Thomas C.W. Landgrebe's work include Geochemistry and Geologic Mapping (7 papers), Imbalanced Data Classification Techniques (7 papers) and Anomaly Detection Techniques and Applications (7 papers). Thomas C.W. Landgrebe is often cited by papers focused on Geochemistry and Geologic Mapping (7 papers), Imbalanced Data Classification Techniques (7 papers) and Anomaly Detection Techniques and Applications (7 papers). Thomas C.W. Landgrebe collaborates with scholars based in Australia, Netherlands and Norway. Thomas C.W. Landgrebe's co-authors include Robert P. W. Duin, R. Dietmar Müller, Rpw Duin, Pavel Paclı́k, Simon Williams, Joanne M. Whittaker, David M. J. Tax, Bernhard S. A. Schuberth, Adriana Dutkiewicz and Grace E. Shephard and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Earth and Planetary Science Letters.

In The Last Decade

Thomas C.W. Landgrebe

19 papers receiving 509 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas C.W. Landgrebe Australia	9	188	187	62	52	47	19	532
Anindya Roy India	15	373 2.0×	425 2.3×	52 0.8×	40 0.8×	59 1.3×	45	866
K. Veeraswamy India	14	75 0.4×	472 2.5×	132 2.1×	23 0.4×	33 0.7×	67	775
Jean Roy Canada	14	204 1.1×	182 1.0×	17 0.3×	131 2.5×	92 2.0×	55	625
Simon O’Callaghan Australia	11	215 1.1×	50 0.3×	150 2.4×	8 0.2×	78 1.7×	16	544
W.K. Stewart United States	12	68 0.4×	54 0.3×	71 1.1×	38 0.7×	42 0.9×	30	528
Ying Lin China	12	343 1.8×	99 0.5×	179 2.9×	28 0.5×	20 0.4×	50	733
Sheng Zhang China	14	88 0.5×	421 2.3×	16 0.3×	40 0.8×	26 0.6×	77	725
James G. Smith United States	12	170 0.9×	176 0.9×	14 0.2×	11 0.2×	55 1.2×	33	454

Countries citing papers authored by Thomas C.W. Landgrebe

Since Specialization

Citations

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

Fields of papers citing papers by Thomas C.W. Landgrebe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas C.W. Landgrebe

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

All Works

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19 of 19 papers shown

Merdith, Andrew, Thomas C.W. Landgrebe, & R. Dietmar Müller. (2015). Prospectivity of Western Australian iron ore from geophysical data using a reject option classifier. Ore Geology Reviews. 71. 761–776. 5 indexed citations

Landgrebe, Thomas C.W. & R. Dietmar Müller. (2015). Uncovering the relationship between subducting bathymetric ridges and volcanic chains with significant earthquakes using geophysical data mining. Australian Journal of Earth Sciences. 62(2). 171–180. 4 indexed citations

Whittaker, Joanne M., Simon Williams, Sheona Masterton, et al.. (2013). Interactions among plumes, mantle circulation and mid-ocean ridges. AGUFM. 2013. 2 indexed citations

Dutkiewicz, Adriana, Thomas C.W. Landgrebe, & Patrice Rey. (2013). Origin of silica and fingerprinting of Australian sedimentary opals. Gondwana Research. 27(2). 786–795. 14 indexed citations

Merdith, Andrew, Thomas C.W. Landgrebe, Adriana Dutkiewicz, & R. Dietmar Müller. (2013). Towards a predictive model for opal exploration using a spatio-temporal data mining approach. Australian Journal of Earth Sciences. 60(2). 217–229. 8 indexed citations

Landgrebe, Thomas C.W., Andrew Merdith, Adriana Dutkiewicz, & R. Dietmar Müller. (2013). Relationships between palaeogeography and opal occurrence in Australia: A data-mining approach. Computers & Geosciences. 56. 76–82. 8 indexed citations

Müller, R. Dietmar & Thomas C.W. Landgrebe. (2012). The link between great earthquakes and the subduction of oceanic fracture zones. Solid Earth. 3(2). 447–465. 25 indexed citations

Qin, Xiaodong, R. Dietmar Müller, John Cannon, et al.. (2012). The GPlates Geological Information Model and Markup Language. SHILAP Revista de lepidopterología. 1(2). 111–134. 17 indexed citations

Qin, Xiaodong, R. Dietmar Müller, John Cannon, et al.. (2012). The GPlates Geological Information Model and Markup Language. 5 indexed citations

10.

Williams, Simon, R. Dietmar Müller, Thomas C.W. Landgrebe, & Joanne M. Whittaker. (2012). An open-source software environment for visualizing and refining plate tectonic reconstructions using high-resolution geological and geophysical data sets. GSA Today. 4–9. 94 indexed citations

11.

Landgrebe, Thomas C.W. & R. Dietmar Müller. (2011). A Spatio-Temporal Knowledge-Discovery Platform for Earth-Science Data. 394–399. 5 indexed citations

12.

Shephard, Grace E., et al.. (2011). Testing absolute plate reference frames and the implications for the generation of geodynamic mantle heterogeneity structure. Earth and Planetary Science Letters. 317-318. 204–217. 63 indexed citations

13.

Paclı́k, Pavel, Carmen Lai, Thomas C.W. Landgrebe, & Robert P. W. Duin. (2010). ROC Analysis and Cost-Sensitive Optimization for Hierarchical Classifiers. lncs 3058. 2977–2980. 1 indexed citations

14.

Landgrebe, Thomas C.W. & Pavel Paclı́k. (2010). The ROC skeleton for multiclass ROC estimation. Pattern Recognition Letters. 31(9). 949–958. 7 indexed citations

15.

Landgrebe, Thomas C.W. & Rpw Duin. (2008). Efficient Multiclass ROC Approximation by Decomposition via Confusion Matrix Perturbation Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. 30(5). 810–822. 82 indexed citations

16.

Landgrebe, Thomas C.W. & Robert P. W. Duin. (2007). Approximating the multiclass ROC by pairwise analysis. Pattern Recognition Letters. 28(13). 1747–1758. 65 indexed citations

17.

Landgrebe, Thomas C.W. & Rpw Duin. (2007). A simplified volume under the roc hypersurface. SAIEE Africa Research Journal. 98(3). 94–100. 5 indexed citations

18.

Landgrebe, Thomas C.W., Pavel Paclı́k, & Robert P. W. Duin. (2006). Precision-recall operating characteristic (P-ROC) curves in imprecise environments. 123–127. 66 indexed citations

19.

Landgrebe, Thomas C.W., David M. J. Tax, Pavel Paclı́k, & Robert P. W. Duin. (2006). The interaction between classification and reject performance for distance-based reject-option classifiers. Pattern Recognition Letters. 27(8). 908–917. 56 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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