Motivated by this, a number of artificial intelligence (AI) systems based on deep learning have been proposed and results have been shown to be quite promising in terms of accuracy in detecting patients infected with COVID-19 using chest radiography images.
Contrastive unsupervised learning has recently shown encouraging progress, e. g., in Momentum Contrast (MoCo) and SimCLR.
#4 best model for Self-Supervised Image Classification on ImageNet
This enables building a large and consistent dictionary on-the-fly that facilitates contrastive unsupervised learning.
#6 best model for Self-Supervised Image Classification on ImageNet
We introduce Stanza, an open-source Python natural language processing toolkit supporting 66 human languages.
This large scale study focuses on quantifying what X-rays diagnostic prediction tasks generalize well across multiple different datasets.
We present a modern scalable reinforcement learning agent called SEED (Scalable, Efficient Deep-RL).