Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
Image data is as common as textual data in this digital world. There is an urgent demand of image management tools as efficient as those text search engines. Decades of research on...
In this paper, we explore the concept of a "library of brain images", which implies not only a repository of brain images, but also efficient search and retrieval mechan...
Bing Bai, Paul B. Kantor, Nicu D. Cornea, Deborah ...
We present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. Our formulation provides answers to...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...
This paper introduces a faceted model of image semantics which attempts to express the richness of semantic content interpretable within an image. Using a large image data-set fro...
Jonathon S. Hare, Paul H. Lewis, Peter G. B. Enser...