Addressing Class Imbalance Problem in Semantic Segmentation Using Binary Focal Loss
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3559-4_28
Reference15 articles.
1. Megahed FM, Chen YJ, Megahed A, Ong Y, Altman N, Krzywinski M (2021) The class imbalance problem. Nat Methods 18(11):1270–1272. https://doi.org/10.1038/s41592-021-01302-4
2. Raghuwanshi BS, Shukla S (2018) Class-specific extreme learning machine for handling binary class imbalance problem. Neur Netw Official J Int Neur Netw Soc 105:206–217. https://doi.org/10.1016/j.neunet.2018.05.011
3. Desuky AS, Hussain S (2021) An improved hybrid approach for handling class imbalance problem. Arab J Sci Eng 46(4):3853–3864. https://doi.org/10.1007/s13369-021-05347-7
4. Wang D, Wu H (2021) IoU regression with H+L-sampling for accurate detection confidence. Sensors (Basel, Switzerland) 21(13):4433. https://doi.org/10.3390/s21134433
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