11 lines
1.1 KiB
TeX
11 lines
1.1 KiB
TeX
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\section{Discussion \& Conclusion}
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\label{sec:conclusion}
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We introduce \schemename, a novel data augmentation scheme that facilitates improved Transformer training for image classification.
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By explicitly separating and recombining foreground objects and backgrounds, \schemename enables controlled data augmentation beyond existing image compositions, leading to significant performance gains on ImageNet and downstream fine-grained classification tasks.
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Furthermore, \schemename provides a powerful framework for analyzing model behavior and quantifying biases, including background robustness, foreground focus, center bias, and size bias.
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Our experiments demonstrate that training using \schemename not only boosts accuracy but also significantly reduces these biases, resulting in more robust and generalizable models.
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In the future, we see \schemename be also applied to other datasets and tasks, like video recognition or segmentation.
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\schemename's ability to both improve performance and provide insights into model behavior makes it a valuable tool for advancing CV research and developing more reliable AI systems.
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