Dataset Open Access
Kaivan Kamali
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.4697906</identifier> <creators> <creator> <creatorName>Kaivan Kamali</creatorName> <affiliation>Penn State University</affiliation> </creator> </creators> <titles> <title>Image classification in Galaxy with MNIST handwritten digits dataset</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2021</publicationYear> <subjects> <subject>Galaxy</subject> <subject>MNIST</subject> <subject>Classification</subject> </subjects> <dates> <date dateType="Issued">2021-04-16</date> </dates> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/4697906</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4697905</relatedIdentifier> </relatedIdentifiers> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><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></description> <description descriptionType="Other">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/</description> </descriptions> </resource>
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