Deep learning high-content imaging is rapidly reshaping image-based screening in the modern laboratory environment. As high-content screening (HCS) generates increasingly large and complex datasets, ...

A new explainable deep learning framework could help greenhouse operators forecast crop yields and energy use more accurately while showing which environmental factors drive those predictions, ...

Abstract: This paper provides an in-depth review of recent advancements in image super-resolution (SR) techniques using deep learning, with a specific focus on their applications in medical imaging.

The era of A.I. propaganda is here — and President Trump is an enthusiastic participant. After nationwide protests this weekend against Mr. Trump’s administration, the president posted an ...

Abstract: Image Super-Resolution (SR) has emerged as a critical task in various domains, allowing low-resolution (LR) photographs to be improved into their high-resolution (HR) equivalents. This study ...

The significant contributions of this work are threefold. First, it leverages deep learning to extend in vivo imaging depth of two-photon excitation fluorescence microscopy, far beyond the depths ...