Data

Data set for a comprehensive tutorial on the SOM-RPM toolbox for MATLAB

La Trobe University
Ben Muir (Aggregated by) David Winkler (Aggregated by) Davide Ballabio (Aggregated by) Paul Pigram (Aggregated by) Sarah Bamford (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26181/25648905.v2&rft.title=Data set for a comprehensive tutorial on the SOM-RPM toolbox for MATLAB&rft.identifier=10.26181/25648905.v2&rft.publisher=La Trobe University&rft.description=This data set is uploaded as supporting information for the publication entitled:A Comprehensive Tutorial on the SOM-RPM Toolbox for MATLABThe attached file 'case_study' includes the following:X : Data from a ToF-SIMS hyperspectral image. A stage raster containing 960 x800 pixels with 963 associated m/z peaks.pk_lbls: The m/z label for each of the 963 m/z peaks.mdl and mdl_masked: SOM-RPM models created using the SOM-RPM tutorial provided within the cited article.Additional details about the datasets can be found in the published article.V2 - contains modified peak lists to show intensity weighted m/z rather than peak midpoint. If you use this data set in your work, please cite our work as follows:[LINK TO BE ADDED TO PAPER ONCE DOI RECEIVED]&rft.creator=Ben Muir&rft.creator=David Winkler&rft.creator=Davide Ballabio&rft.creator=Paul Pigram&rft.creator=Sarah Bamford&rft.creator=Wil Gardner&rft.date=2024&rft_rights= https://creativecommons.org/licenses/by-nc-sa/4.0/&rft_rights=© The Authors 2024. This manuscript version is made available under the CC-BY-NC-SA 4.0 license:https://creativecommons.org/licenses/by-nc-sa/4.0/. This license lets others remix, adapt, and build upon your work non-commercially, as long as they credit you and license their new creations under the identical terms.&rft_subject=Physical sciences&rft_subject=Mathematical sciences&rft_subject=Other physical sciences&rft_subject=Machine learning&rft_subject=ToF-SIMS hyperspectral imaging data&rft_subject=self-organising map (SOM)&rft_subject=surface analysis&rft_subject=machiene learning&rft_subject=inkjet ink&rft_subject=inkjet printing&rft_subject=Hyperspectral dataset&rft.type=dataset&rft.language=English Access the data
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https://creativecommons.org/licenses/by-nc-sa/4.0/

© The Authors 2024. This manuscript version is made available under the CC-BY-NC-SA 4.0 license:https://creativecommons.org/licenses/by-nc-sa/4.0/. This license lets others remix, adapt, and build upon your work non-commercially, as long as they credit you and license their new creations under the identical terms.

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This data set is uploaded as supporting information for the publication entitled:

A Comprehensive Tutorial on the SOM-RPM Toolbox for MATLAB


The attached file 'case_study' includes the following:

X : Data from a ToF-SIMS hyperspectral image. A stage raster containing 960 x800 pixels with 963 associated m/z peaks.

pk_lbls: The m/z label for each of the 963 m/z peaks.

mdl and mdl_masked: SOM-RPM models created using the SOM-RPM tutorial provided within the cited article.

Additional details about the datasets can be found in the published article.

V2 - contains modified peak lists to show intensity weighted m/z rather than peak midpoint.

If you use this data set in your work, please cite our work as follows:

[LINK TO BE ADDED TO PAPER ONCE DOI RECEIVED]

Issued: 22 08 2024

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Hyperspectral dataset | Machine learning | Mathematical sciences | Other physical sciences | Physical sciences | ToF-SIMS hyperspectral imaging data | inkjet ink | inkjet printing | machiene learning | self-organising map (SOM) | surface analysis |

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