To tackle the above issue, we present a multilevel contrastive graph masked autoencoder (MCGMAE) for unsupervised GSL. Specifically, we first introduce a graph masked autoencoder with the dual feature ...

The below image is a representation of the basic structure of the mask autoencoder. Image source. A similar method is applied in the Masked Autoencoders Are Scalable Vision Learners work. Model and ...

Furthermore, these methods have limited generalization capacity, requiring additional manual labels to be generated for each dataset and use case. We introduce MAESTER (Masked AutoEncoder guided ...

Keywords: neural segmentation, SEM image, masked autoencoder, image segmentation, self-supervised learning. Citation: Cheng A, Shi J, Wang L and Zhang R (2023) Learning the heterogeneous ...

Design a patches masked autoencoder by CNN. Contribute to JJLi0427/CNN_Masked_Autoencoder development by creating an account on GitHub. ... Model Structure. The design involves two stages of work. In ...

The repository gives an improved Transformer-ConvNet architecture with Masked AutoEncoder for Cardiac MRI Registration. The core of the Transformer is designed as a Masked AutoEncoder (MAE) and a ...

In recent years, masked autoencoder (MAE) has been used in various fields due to its powerful self-supervised learning ability and has achieved good results in masked data reconstruction tasks.