PUBLIC MARKS from decembre with tags research & person

The Google Labs N-gram Viewer is the first tool of its kind, capable of precisely and rapidly quantifying cultural trends based on massive quantities of data. It is a gateway to culturomics! The browser is designed to enable you to examine the frequency of words (banana) or phrases ('United States of America') in books over time. You'll be searching through over 5.2 million books: ~4% of all books ever published! There are lots of different things you can check, like your favorite word (Supercalifragilisticexpialidocious) or person (President Taft; Chief Justice Taft) or part of the holiday (Christmas Tree).

Overview: The following overview shows the workflow for a single input image of Sylvestor Stallone from the publicly available LFW dataset. Detect faces with a pre-trained models from dlib or OpenCV. Transform the face for the neural network. This repository uses dlib's real-time pose estimation with OpenCV's affine transformation to try to make the eyes and bottom lip appear in the same location on each image. Use a deep neural network to represent (or embed) the face on a 128-dimensional unit hypersphere. The embedding is a generic representation for anybody's face. Unlike other face representations, this embedding has the nice property that a larger distance between two face embeddings means that the faces are likely not of the same person. This property makes clustering, similarity detection, and classification tasks easier than other face recognition techniques where the Euclidean distance between features is not meaningful. Apply your favorite clustering or classification techniques to the features to complete your recognition task. See below for our examples for classification and similarity detection, including an online web demo.