Real-world datasets are often highly class-imbalanced, which can adversely impact the performance of deep learning models. The majority of research on training neural networks …
J Kim, J Jeong, J Shin - … of the IEEE/CVF conference on …, 2020 - openaccess.thecvf.com
In most real-world scenarios, labeled training datasets are highly class-imbalanced, where deep neural networks suffer from generalizing to a balanced testing criterion. In this paper …
Y Yang, Z Xu - Advances in neural information processing …, 2020 - proceedings.neurips.cc
Real-world data often exhibits long-tailed distributions with heavy class imbalance, posing great challenges for deep recognition models. We identify a persisting dilemma on the value …
S Ahn, J Ko, SY Yun - arXiv preprint arXiv:2302.05499, 2023 - arxiv.org
Class imbalance problems frequently occur in real-world tasks, and conventional deep learning algorithms are well known for performance degradation on imbalanced training …
HJ Ye, DC Zhan, WL Chao - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
Neural networks trained with class-imbalanced data are known to perform poorly on minor classes of scarce training data. Several recent works attribute this to over-fitting to minor …
J Gao, H Zhao, D dan Guo, H Zha - Forty-first International …, 2024 - openreview.net
A well-trained deep neural network on balanced datasets usually exhibits the Neural Collapse (NC) phenomenon, which is an informative indicator of the model achieving good …
H Rangwani, SK Aithal… - Advances in Neural …, 2022 - proceedings.neurips.cc
Real-world datasets exhibit imbalances of varying types and degrees. Several techniques based on re-weighting and margin adjustment of loss are often used to enhance the …
X Liu, J Zhang, T Hu, H Cao, Y Yao… - … Conference on Artificial …, 2023 - proceedings.mlr.press
Although deep neural networks achieve tremendous success on various classification tasks, the generalization ability drops sheer when training datasets exhibit long-tailed distributions …
P Chu, X Bian, S Liu, H Ling - … Conference, Glasgow, UK, August 23–28 …, 2020 - Springer
Real-world data often follow a long-tailed distribution as the frequency of each class is typically different. For example, a dataset can have a large number of under-represented …