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

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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Bibliographic Details
Main Authors: Leopold Fischer-Brandies, Lucas Muller, Benjamin Rebholz, Ricardo Buettner
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Robustness
training data
deep learning
transfer learning
OCR
handwriting
Online Access:https://ieeexplore.ieee.org/document/10946162/
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