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» Exploiting multiple classifier types with active learning
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IGARSS
2009
13 years 5 months ago
Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
Alexander Liu, Goo Jun, Joydeep Ghosh
INTERACT
2007
13 years 8 months ago
DeskJockey: Exploiting Passive Surfaces to Display Peripheral Information
This paper describes DeskJockey, a system to provide users with additional display space by projecting information on passive physical surfaces in the environment. The current Desk...
Ryder Ziola, Melanie Kellar, Kori Inkpen
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 8 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
ICPR
2002
IEEE
14 years 8 months ago
View-Based Dynamic Object Recognition Based on Human Perception
Psychophysical studies have shown that humans actively exploit temporal information such as contiguity of images in object recognition. We have recently developed a recognition sy...
Arnulf B. A. Graf, Christian Wallraven, Heinrich H...
KDD
2002
ACM
93views Data Mining» more  KDD 2002»
14 years 7 months ago
Interactive deduplication using active learning
Deduplication is a key operation in integrating data from multiple sources. The main challenge in this task is designing a function that can resolve when a pair of records refer t...
Sunita Sarawagi, Anuradha Bhamidipaty