Abstract: Super resolution (SR) is an ill-posed problem because one low-resolution image can correspond to multiple high-resolution images. High-frequency details are significantly lost in ...

In this guest blog, Karen McNulty Walsh of Brookhaven National Laboratory explains how Michigan Technological University scientists and alumni developed an innovative, centimeter-scale view into ...

Images lose quality in multiple ways. Some lose their resolution and gradually degrade with each share. Some lose clarity, some go out of style through over-editing, and physical photos may lose shape ...

Newly released high-resolution images have revealed Jupiter’s moon Callisto in extraordinary detail. The surface features visible in these images show an ancient world shaped by billions of years of ...

Abstract: While transformers are powerful neural network architectures for feature learning, current Transformer-based approaches for semantic segmentation of high-resolution remote sensing images ...