V2.11.0
Change Log
Feature
- Implement PAdam optimizer (#186)
- Implement LOMO optimizer (#188)
- Implement loss functions (#189)
- BCELoss
- BCEFocalLoss
- FocalLoss : Focal Loss for Dense Object Detection
- FocalCosineLoss : Data-Efficient Deep Learning Method for Image Classification Using Data Augmentation, Focal Cosine Loss, and Ensemble
- DiceLoss : Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations
- LDAMLoss : Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
- JaccardLoss
- BiTemperedLogisticLoss : Robust Bi-Tempered Logistic Loss Based on Bregman Divergences