The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data

The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data

Errors in measurements are key to weighting the value of data, but are often neglected in machine learning (ML). We show how convolutional neural networks (CNNs) are able to learn about the context and patterns of signal and noise, leading to improvements in the performance of classification methods...

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Detaylı Bibliyografya
Asıl Yazarlar: Natália V N Rodrigues, L Raul Abramo, Nina S T Hirata
Materyal Türü: Makale
Dil:English
Baskı/Yayın Bilgisi: IOP Publishing 2023-01-01
Seri Bilgileri:Machine Learning: Science and Technology
Konular:
machine learning methods
statistical techniques
scientific data analysis
Online Erişim:https://doi.org/10.1088/2632-2153/ad0285

Internet

https://doi.org/10.1088/2632-2153/ad0285

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