2024-03-28T11:56:44Z
https://b2share.eudat.eu/api/oai2d
oai:b2share.eudat.eu:b2rec/37c30138588f4ae6a806f3142d696f81
2018-01-11T13:48:28Z
e9b9792e-79fb-4b07-b6b4-b9c2bd06d095
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17218542
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20180111134828.0
piSVM version 1.2.1
Deployment JUDGE cluster of the
Juelich Supercomputing Centre in Germany
Parallel Support Vector Machine (SVM)
classification runs to analyse
remote sensing hyperspectral images
(52 land cover classes, 30 features).
Indian processed: 1417x614x30 (training 10% and test)
Data preprocessed with PCA, ESDAP, NWFE.
Parameters have been optimized using 10-fold cross-validation, more information available at:
http://hdl.handle.net/11304/5bba8e36-fe63-11e4-8a18-f31aa6f4d448
Supplemental material for paper study.
Corresponding dataset (processed) available at:
http://hdl.handle.net/11304/7e8eec8e-ad61-11e4-ac7e-860aa0063d1f
Morris Riedel
Remote sensing
en
37c30138588f4ae6a806f3142d696f81
SVM
remote sensing
analytics
MPI
classification
http://hdl.handle.net/11304/c528998e-ff7c-11e4-8a18-f31aa6f4d448
234
http://hdl.handle.net/11304/fd4629e7-a9dc-4790-8565-a53acc70a7c9
http://b2share.eudat.eu
2015-05-17
piSVM1.2.1 Analytics Training (10x-CV optimized) Indian Pines Images Processed 30 Features 52 Classes