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Converting tabular data into images for deep learning with convolutional neural networks

Abstract Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features, such as speech and imaging. However, most tabular data do not assume a spatial relationship between features, and thus are unsui...

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Bibliografische Detailangaben
Hauptverfasser: Yitan Zhu, Thomas Brettin, Fangfang Xia, Alexander Partin, Maulik Shukla, Hyunseung Yoo, Yvonne A. Evrard, James H. Doroshow, Rick L. Stevens
Format: Artigo
Sprache:Inglês
Veröffentlicht: Nature Portfolio 2021-05-01
Schriftenreihe:Scientific Reports
Online-Zugang:https://doi.org/10.1038/s41598-021-90923-y
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