Effect of Multimodal Metadata Augmentation on Classification Performance in Deep Learning
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9436-6_27
Reference20 articles.
1. Abdollahi B, Tomita N, Hassanpour S (2020) Data augmentation in training deep learning models for medical image analysis. In: Deep learners and deep learner descriptors for medical applications, pp 167–180
2. Atasever S, Azgınoglu N, Terzı DS, Terzı R (2022) A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning. In: Clinical imaging
3. Bhardwaj C, Jain S, Sood M (2021) Hierarchical severity grade classification of non-proliferative diabetic retinopathy. J Ambient Intell Humanized Comput 12:2649–2670
4. Chen Y, Yang XH, Wei Z, Heidari AA, Zheng N, Li Z, Chen H, Hu H, Zhou Q, Guan Q (2022) Generative adversarial networks in medical image augmentation: a review. Comput Biol Med 144:105382
5. Gordienko Y, Shulha M, Kochura Y, Rokovyi O, Alienin O, Stirenko S (2023) Fuzzy metadata augmentation for multimodal data classification. In: Mobile computing and sustainable informatics: proceedings of ICMCSI 2023. Springer, Heidelberg, pp 157–172
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