Notifications You must be signed in to change notification settings Implementation of ResNet 50, 101, 152 in PyTorch based on paper "Deep Residual Learning for Image Recognition" by Kaiming He, ...

The problem of imbalanced data is also crucial for achieving model generalization. This paper proposes a hybrid attention-based ResNet architecture for ICH detection and classification. An attention ...

Self-supervised learning approaches, such as masked autoencoder (MAE) reconstruction and contrastive learning, offer a promising solution by reducing reliance on labeled data. Nonetheless, transformer ...

15 available encoders All encoders have pre-trained weights for faster and better convergence 35% or more inference speed boost compared with pytorch cuda, same speed for cpu. (Unet tested in rtx ...