We propose to shift the goal of recognition from naming
to describing. Doing so allows us not only to name familiar
objects, but also: to report unusual aspects of a familiar
ob...
Ali Farhadi, David A. Forsyth, Derek Hoiem, Ian En...
Human-nameable visual “attributes” can benefit various recognition tasks. However, existing techniques restrict these properties to categorical labels (for example, a person ...
We present a method to learn visual attributes (eg.“red”,
“metal”, “spotted”) and object classes (eg. “car”,
“dress”, “umbrella”) together. We assume imag...
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
The reasoning tasks that can be performed with semantic web service descriptions depend on the quality of the domain ontologies used to create these descriptions. However, buildin...
Marta Sabou, Chris Wroe, Carole A. Goble, Gilad Mi...