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» Pruning Training Sets for Learning of Object Categories
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IROS
2008
IEEE
129views Robotics» more  IROS 2008»
14 years 3 months ago
Recognizing texture and hardness by touch
Abstract— We have experimented with different neural network based architectures for bio-inspired self-organizing texture and hardness perception systems. To this end we have dev...
Magnus Johnsson, Christian Balkenius
SCIA
2005
Springer
186views Image Analysis» more  SCIA 2005»
14 years 2 months ago
Building Detection from Mobile Imagery Using Informative SIFT Descriptors
We propose reliable outdoor object detection on mobile phone imagery from off-the-shelf devices. With the goal to provide both robust object detection and reduction of computation...
Gerald Fritz, Christin Seifert, Manish Kumar, Luca...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 9 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
TSP
2010
13 years 3 months ago
Learning graphical models for hypothesis testing and classification
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
AUSAI
2008
Springer
13 years 11 months ago
Learning a Generative Model for Structural Representations
Abstract. Graph-based representations have been used with considercess in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the ...
Andrea Torsello, David L. Dowe