Unlike other deep learning (DL) models, Transformer has the ability to extract long-range dependency features from hyperspectral image (HSI) data. Masked autoencoder (MAE), which is based on ...

Masked autoencoders are type of autoencoder where the process of data masking is used with autoencoders to make autoencoder more resilient.

Instructional Mask Autoencoder: A Scalable Learner for Hyperspectral Image Classification Abstract: Nowadays, an increasing number of hyperspectral images (HSIs) are becoming available. However, the ...

masked image modelling can provide competitive results to the other approaches like contrastive learning. Performing computer vision tasks using masked images can be called masked image modelling.

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 ...

Inspired from the pretraining algorithm of BERT (Devlin et al.), they mask patches of an image and, through an autoencoder predict the masked patches. In the spirit of "masked language modeling", this ...

The masked autoencoder is a self-supervised learning method that learns representations from the image itself. DAE (Vincent et al., 2008, 2010) is a pioneering work in this field that presents masking ...