ACCV
2010
Springer
13 years 9 months ago
2010
Springer
We present a new active learning approach to incorporate
human feedback for on-line unusual event detection. In contrast to most
existing unsupervised methods that perform passiv...
CVPR
2011
IEEE
13 years 9 months ago
2011
IEEE
In this work, we present an active-learning algorithm for piecewise planar 3D reconstruction of a scene. While previous interactive algorithms require the user to provide tedious i...
CVPR
2011
IEEE
13 years 10 months ago
2011
IEEE
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
ICIP
2009
IEEE
13 years 10 months ago
2009
IEEE
Active learning is a framework that has attracted a lot of research interest in the content-based image retrieval (CBIR) in recent years. To be effective, an active learning syste...
ICDM
2009
IEEE
13 years 10 months ago
2009
IEEE
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed images usually cover large geographical areas, and s...
EMNLP
2009
13 years 10 months ago
2009
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
ACL
2009
13 years 10 months ago
2009
While Active Learning (AL) has already been shown to markedly reduce the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned a...
PKDD
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. When faced with the task of building accurate classifiers, active learning is often a beneficial tool for minimizing the requisite costs of human annotation. Traditional ...
PKDD
2010
Springer
13 years 10 months ago
2010
Springer
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
CEC
2010
IEEE
13 years 11 months ago
2010
IEEE
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...