Visual scene understanding: A Bayesian approach
Abstract
Despite impressive progress in machine learning techniques over the last decade, current approaches fall far short of the capabiliti"es of primate vision. These approaches rely mainly on brute-force learning of massive training sets. This is not only costly but als"o results in brittle systems that can fail spectacularly. In contrast, perception in humans and other primates structures the input"" by learning object categories from a small number of observations. To gain insight how this is achieved, we will use probabilistic" Bayesian methods to use context information to learn object categories and relations between objects and their parts.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 26, 2018
- Source ID
- N000141812136
Entities
People
- Ernst Niebur
Organizations
- Johns Hopkins University
- Office of Naval Research
- United States Navy