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COLING
2010
13 years 2 months ago
A Comparison of Models for Cost-Sensitive Active Learning
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Katrin Tomanek, Udo Hahn
BMVC
2010
13 years 5 months ago
A general boosting-based framework for active object recognition
We propose a novel general framework with a boosting algorithm to achieve active object classification by view selection. The proposed framework actively decides the next best vie...
Zhaoyin Jia, Yao-Jen Chang, Tsuhan Chen
NAACL
2003
13 years 9 months ago
Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
Shona Douglas
IJON
2007
131views more  IJON 2007»
13 years 7 months ago
Margin-based active learning for LVQ networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples and thereby increase speed a...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
IVC
2010
143views more  IVC 2010»
13 years 6 months ago
Video-based face model fitting using Adaptive Active Appearance Model
Active Appearance Model (AAM) represents the shape and appearance of an object via two low-dimensional subspaces, one for shape and one for appearance. AAM for facial images is cu...
Xiaoming Liu