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FGR
2006
IEEE
147views Biometrics» more  FGR 2006»
14 years 3 months ago
Learning Sparse Features in Granular Space for Multi-View Face Detection
In this paper, a novel sparse feature set is introduced into the Adaboost learning framework for multi-view face detection (MVFD), and a learning algorithm based on heuristic sear...
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
FGR
2008
IEEE
254views Biometrics» more  FGR 2008»
13 years 10 months ago
Design sparse features for age estimation using hierarchical face model
A key point in automatic age estimation is to design feature set essential to age perception. To achieve this goal, this paper builds up a hierarchical graphical face model for fa...
Jin-Li Suo, Tianfu Wu, Song Chun Zhu, Shiguang Sha...
ICML
2000
IEEE
14 years 9 months ago
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
ITNG
2010
IEEE
14 years 2 months ago
Middleware Specialization for Product-Lines Using Feature-Oriented Reverse Engineering
Supporting the varied software feature requirements of multiple variants of a software product-line while promoting reuse forces product line engineers to use general-purpose, fea...
Akshay Dabholkar, Aniruddha S. Gokhale
ICASSP
2010
IEEE
13 years 9 months ago
Boosted binary features for noise-robust speaker verification
The standard approach to speaker verification is to extract cepstral features from the speech spectrum and model them by generative or discriminative techniques. We propose a nov...
Anindya Roy, Mathew Magimai-Doss, Sébastien...