Warick Brown

684 citations
22 papers · 607 · h-index 10

Impact in

Papers in

Warick Brown

21 papers receiving 578 citations

Peers

Warick Brown
Comparison fields: 5 of 73
  • Media Technology 160
  • Artificial Intelligence 484
  • Environmental Engineering 186
  • Geophysics 144
  • Geochemistry and Petrology 50
Replace Ryoichi Kouda with:
Ryoichi Kouda Japan
Guocheng Pan United States
C. M. Knox‐Robinson Australia
Fan Xiao China
Xiaohui Li China
Ehsan Farahbakhsh Australia
Daniel Wedge Australia
Donald A. Singer United States
Ernst Schetselaar Canada
Warick Brown relative to Ryoichi Kouda Japan Ryoichi Kouda's profile →
Citations per field
00.5×2.6×
Ryoichi Kouda · 1×
Citations per year

Countries citing papers authored by Warick Brown

Since Specialization
Citations

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

Fields of papers citing papers by Warick Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Warick Brown, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Warick Brown Line = papers co-authored together Warick Brown links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000286
2 200365
3 200365
4 198655
5 200828
6 199719
7 198415
8 200312
9 198310
10 20069
11 20058
12 20207
13
Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping
20026
14
Mineral prospectivity prediction using interval neutrosophic sets
20064
15 20044
16 20064
17 20063
18 20032
19 20052
20 20251

About Warick Brown

Warick Brown is a scholar working on Artificial Intelligence, Mechanical Engineering, Media Technology, Geophysics and Environmental Engineering, having authored 22 papers that have together received 607 indexed citations. Recurring topics across this work include Geochemistry and Geologic Mapping (21 papers), Mineral Processing and Grinding (11 papers), Remote-Sensing Image Classification (7 papers), Soil Geostatistics and Mapping (5 papers), Geophysical and Geoelectrical Methods (3 papers), Geological and Geochemical Analysis (3 papers), Neural Networks and Applications (3 papers) and earthquake and tectonic studies (2 papers). The work is most often cited by research in Media Technology (160 citations), Artificial Intelligence (484 citations), Environmental Engineering (186 citations), Geophysics (144 citations) and Geochemistry and Petrology (50 citations). Warick Brown has collaborated with scholars based in Australia and Japan. Frequent co-authors include David I. Groves, Robert G. Barnes, Tom Gedeon, T.D. Gedeon, David Groves, T. A. P. Kwak, Chun Che Fung, Stephen Fraser, F. P. Bierlein and Adrian Baddeley. Their work appears in journals such as Natural Resources Research, Australian Journal of Earth Sciences, International Journal of Remote Sensing, Economic Geology and Computers & Geosciences.

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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