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ICCV
2011
IEEE
12 years 7 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
ICIP
1999
IEEE
14 years 9 months ago
Perceptual Grouping of 3-D Features in Aerial Image Using Decision Tree Classifier
We address a new perceptual grouping algorithmfor aerial images, which employs a decision tree classifier and hierarchical multilevel grouping strategy an a bottom-up fashion. In ...
In Kyu Park, Kyoung Mu Lee, Sang Uk Lee
ECCV
2010
Springer
14 years 20 days ago
Stacked Hierarchical Labeling
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
WWW
2007
ACM
14 years 8 months ago
Hierarchical, perceptron-like learning for ontology-based information extraction
Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, ver...
Yaoyong Li, Kalina Bontcheva
GPEM
2008
128views more  GPEM 2008»
13 years 7 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood