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TIP
2010
155views more  TIP 2010»
14 years 8 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
CHI
2006
ACM
15 years 10 months ago
Active CyberCode: a directly controllable 2D code
Many augmented reality (AR) applications which overlay computer graphics on a real image have been developed. One of the limitations of such applications is that a user has to con...
Yuji Ayatsuka, Jun Rekimoto
PKDD
2009
Springer
174views Data Mining» more  PKDD 2009»
15 years 4 months ago
Active and Semi-supervised Data Domain Description
Data domain description techniques aim at deriving concise descriptions of objects belonging to a category of interest. For instance, the support vector domain description (SVDD) l...
Nico Görnitz, Marius Kloft, Ulf Brefeld
KCAP
2009
ACM
15 years 4 months ago
Reducing class imbalance during active learning for named entity annotation
In lots of natural language processing tasks, the classes to be dealt with often occur heavily imbalanced in the underlying data set and classifiers trained on such skewed data t...
Katrin Tomanek, Udo Hahn
PREMI
2007
Springer
15 years 4 months ago
Segmenting Multiple Textured Objects Using Geodesic Active Contour and DWT
We address the issue of segmenting multiple textured objects in presence of a background texture. The proposed technique is based on Geodesic Active Contour (GAC) and can segment m...
Surya Prakash, Sukhendu Das