We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
This paper proposes a learnt data-driven approach for accurate, real-time tracking of facial features using only intensity information. Constraints such as a-priori shape models o...
Eng-Jon Ong, Yuxuan Lan, Barry Theobald, Richard H...
Feature selection is an important data preprocessing step in data mining and pattern recognition. Many algorithms have been proposed in the past for simple patterns that can be cha...
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
In this work we strive to find an optimal set of acoustic features for the discrimination of speech, monophonic singing, and polyphonic music to robustly segment acoustic media st...