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Arxiv
1d
236
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Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
- The impact of duplicated training data in image classification models has been studied.
- Duplicated images in the training set negatively affect model training efficiency.
- The presence of duplicated images may result in lower accuracy of the image classifier.
- Even when duplicated samples are selected uniformly, accuracy does not significantly improve.
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