Studying the solar system and especially the Sun relies on the data gathered daily from
space missions. These missions are data-intensive and compressing this data to make them …

NASA's Solar Dynamics Observatory (SDO) mission gathers 1.4 terabytes of data each day
from its geosynchronous orbit in space. SDO data includes images of the Sun captured at …

NASA's Solar Dynamics Observatory (SDO) mission collects extensive data to monitor the
Sun's daily activity. In the realm of space mission design, data compression plays a crucial …

NASA's Solar Dynamics Observatory (SDO) mission collects large data volumes of the Sun's
daily activity. Data compression is crucial for space missions to reduce data storage and …

Recently, convolutional neural networks have been successfully applied to lossy image
compression. End-to-end optimized autoencoders, possibly variational, are able to …

In recent years, neural networks have emerged as data-driven tools to solve problems which
were previously addressed with model-based methods. In particular, image processing has …

In recent years, deep learning has been widely employed in the field of image compression,
the most significant of which is the lossy image compression method on the basis of …

A Transformer-based Image Compression (TIC) approach is developed which reuses the
canonical variational autoencoder (VAE) architecture with paired main and hyper encoder …

Image compression constitutes a significant challenge amid the era of information explosion.
Recent studies employing deep learning methods have demonstrated the superior …

Deep learning-based image compression algorithms typically focus on designing encoding
and decoding networks and improving the accuracy of entropy model estimation to enhance …