Forrest Sheng Bao

TL;DR: The scope of information collections, database constructions, and machine learning techniques (such as deep learning and transfer learning), which may facilitate "Learn and Design" for strain development are highlighted.

TL;DR: Wang et al. as discussed by the authors proposed a hybrid deep learning-machine learning framework to detect patients with COVID-19 using low-dimensional clinical and lab testing data, as well as high-dimensional computed tomography imaging data.

TL;DR: A multi-domain approach that learns domain relationships to help the task by transferring knowledge from data-rich domains to data-deficient domains and gates multi-granularity embeddings in a Neural Network (NN) based transfer learning framework to reflect the domain-variant importance of words.

TL;DR: In this paper, the authors used event-related fMRI to study brain activation preceding purchase decisions under three visual presentation strategies: (1) static picture, (2) image zoom, and (3) rotation video.

TL;DR: A vein imaging system to combine reflectance mode visible spectrum images (VIS) with transmission mode near-infrared (NIR) images in real time that can be applied for IV placement, morphological analysis for disease state detection, and biometric analysis is presented.