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ICDM
2009
IEEE
207views Data Mining» more  ICDM 2009»
15 years 4 months ago
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes
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...
Goo Jun, Ranga Raju Vatsavai, Joydeep Ghosh
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
15 years 10 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
ISMB
1993
15 years 8 months ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
SSD
2005
Springer
173views Database» more  SSD 2005»
16 years 4 days ago
On Discovering Moving Clusters in Spatio-temporal Data
A moving cluster is defined by a set of objects that move close to each other for a long time interval. Real-life examples are a group of migrating animals, a convoy of cars movin...
Panos Kalnis, Nikos Mamoulis, Spiridon Bakiras
ICIP
2006
IEEE
16 years 8 months ago
Adaptive Region-Based Compression of Multispectral Images
The region-based description of multispectral images enables important high-level tasks such as data mining and retrieval, and region-of-interest selection. In order to obtain an ...
Marco Cagnazzo, Raffaele Gaetano, Sara Parrilli, L...