A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
We introduce the Ranked Feature Fusion framework for information retrieval system design. Typical information retrieval formalisms such as the vector space model, the bestmatch mo...
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
Feature models are commonly used to capture the commonality and the variability of product families. There are several feature model notations that correspondingly depict the conce...