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, ...

NicMSlesions makes it easy to accurately segment white matter (WM) lesions on Magnetic Resonance Images (MRI) using supervised deep learning. With nicMSlesions, training and/or inference of a complex ...

This is a tensorflow implementation of "Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network", a deep learning based Single-Image Super-Resolution (SISR) ...

Nvidia’s RTX series include some of the best graphics cards on the market and are known for two flagship features: real-time ray tracing and Deep Learning Super Sampling (DLSS). While ray tracing is ...

Deep learning shows promising results in extracting useful information from medical images. The proposed work applies a Convolutional Neural Network (CNN) on retinal images to extract features that ...

High-quality and high-resolution precipitation products are critically important to many hydrological applications. Advances in satellite remote sensing instruments and data retrieval algorithms ...