Dataset Open Access
Kaivan Kamali
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nmm##2200000uu#4500</leader> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Galaxy</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">MNIST</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Classification</subfield> </datafield> <controlfield tag="005">20210417002724.0</controlfield> <datafield tag="500" ind1=" " ind2=" "> <subfield code="a">Credit: Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based learning applied to document recognition." Proceedings of the IEEE, 86(11):2278-2324, November 1998 http://yann.lecun.com/exdb/mnist/</subfield> </datafield> <controlfield tag="001">4697906</controlfield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">43814873</subfield> <subfield code="z">md5:12f731f0ac1b3197363ae04c555ee704</subfield> <subfield code="u">https://zenodo.org/record/4697906/files/X_test.tsv</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">87764932</subfield> <subfield code="z">md5:946db18725bfdeee7f079706635b5595</subfield> <subfield code="u">https://zenodo.org/record/4697906/files/X_train.tsv</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">12000</subfield> <subfield code="z">md5:ffb3f9bb2640bd078691c51a03416ed2</subfield> <subfield code="u">https://zenodo.org/record/4697906/files/y_test.tsv</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">24000</subfield> <subfield code="z">md5:52e85ce2d279b0dec03f4168959fcb3f</subfield> <subfield code="u">https://zenodo.org/record/4697906/files/y_train.tsv</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2021-04-16</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">openaire_data</subfield> <subfield code="o">oai:zenodo.org:4697906</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="u">Penn State University</subfield> <subfield code="a">Kaivan Kamali</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Image classification in Galaxy with MNIST handwritten digits dataset</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield> <subfield code="a">Creative Commons Attribution 4.0 International</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><p>Credit:&nbsp;Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. &quot;Gradient-based learning applied to document recognition.&quot;&nbsp;Proceedings of the IEEE, 86(11):2278-2324, November 1998<br> <br> This is a subset of MNIST handwritten digits dataset (http://yann.lecun.com/exdb/mnist/). Training data of composed of 12,000 images of digits 0 to 9. Test data is composed of 6,000 images of digits 0 to 9 (Original dataset has 60,000 training and 10,000 testing images. We are using a subset for a Galaxy tutorial, so the training is not too computationally intensive). Images are grayscale and 28 by 28 pixels. Each pixel has a value between 0 and 255 (0 for color black, 255 for color white, and all other values for different shades of gray).&nbsp; &nbsp;</p></subfield> </datafield> <datafield tag="773" ind1=" " ind2=" "> <subfield code="n">doi</subfield> <subfield code="i">isVersionOf</subfield> <subfield code="a">10.5281/zenodo.4697905</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.5281/zenodo.4697906</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">dataset</subfield> </datafield> </record>
All versions | This version | |
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Views | 159 | 159 |
Downloads | 267 | 267 |
Data volume | 9.5 GB | 9.5 GB |
Unique views | 144 | 144 |
Unique downloads | 92 | 92 |