April 1, 2024, 4:44 a.m. | Juhwan Choi, YoungBin Kim

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.20012v1 Announce Type: new
Abstract: Data augmentation is one of the regularization strategies for the training of deep learning models, which enhances generalizability and prevents overfitting, leading to performance improvement. Although researchers have proposed various data augmentation techniques, they often lack consideration for the difficulty of augmented data. Recently, another line of research suggests incorporating the concept of curriculum learning with data augmentation in the field of natural language processing. In this study, we adopt curriculum data augmentation for image …

abstract arxiv augmentation augmented data cs.ai cs.cv curriculum curriculum learning data deep learning image image data improvement line overfitting performance regularization researchers strategies training type

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