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To Combine or Not to Combine? The Influence of Combining Training Datasets on the Robustness of Deep Learning Models: An Analysis for Optical Character Recognition of Handwriting

The present manuscript addresses the question of how training data should be sampled for deep learning models by analyzing and evaluating the impact of training data representation and complexity on the performance and robustness of deep learning models. To address this open question, we take a comb...

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Hlavní autoři: Leopold Fischer-Brandies, Lucas Muller, Benjamin Rebholz, Ricardo Buettner
Médium: Artigo
Jazyk:Inglês
Vydáno: IEEE 2025-01-01
Edice:IEEE Access
Témata:
Robustness
training data
deep learning
transfer learning
OCR
handwriting
On-line přístup:https://ieeexplore.ieee.org/document/10946162/
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