Group optimization for multi-attribute visual embedding
Group optimization for multi-attribute visual embedding is a scholarly work, published in 2018 in ''Visual Informatics''. The main subjects of the publication include image, feature engineering, data mining, question answering, artificial intelligence, transfer learning, similarity, Pairwise comparison, embedding, glossary of archaeology, pattern recognition, and computer science. The authors present a method for learning the semantic visual similarity among images, inferring their latent attributes and embedding them into multi-spaces corresponding to each latent attribute.