2024-03-29T06:25:39Z
https://b2share.eudat.eu/api/oai2d
oai:b2share.eudat.eu:b2rec/9d5da9ade3704cc399c98c62266b039c
2018-01-11T13:48:28Z
e9b9792e-79fb-4b07-b6b4-b9c2bd06d095
Other
open
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1278
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1192
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1147
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653
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1142
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99540318
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782481
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99540318
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782481
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577
http://hdl.handle.net/11304/831185bf-22e1-48fe-9150-b2407e020bbc
1138
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1143
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99540318
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782481
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577
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1139
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650
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213
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212
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212
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212
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213
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213
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213
http://hdl.handle.net/11304/039c9bf4-6b45-4973-aca6-f6a8e1b28307
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914193
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873388
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903569
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925585
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966052
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, 200 features).
Indian raw: 1417x614x200 (training 10% and test)
Parameters have been optimized using 10-fold cross-validation, more information available at:
http://hdl.handle.net/11304/163ba8e8-fe60-11e4-8a18-f31aa6f4d448
Supplemental material for paper study.
Correspondending dataset (raw) available at:
http://hdl.handle.net/11304/7e8eec8e-ad61-11e4-ac7e-860aa0063d1f
Remote sensing
en
9d5da9ade3704cc399c98c62266b039c
SVM
remote sensing
analytics
MPI
classification
http://hdl.handle.net/11304/c06a8c7e-fe6c-11e4-8a18-f31aa6f4d448
233
http://hdl.handle.net/11304/13cee183-b75a-429a-9f18-e9de3637d28a
http://b2share.eudat.eu
2015-05-17
piSVM1.2.1 Analytics Training (10x-CV optimized) Indian Pines Images Raw 200 Features 52 Classes