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IROS
2009
IEEE
205views Robotics» more  IROS 2009»
16 years 1 months ago
Probabilistic categorization of kitchen objects in table settings with a composite sensor
— In this paper, we investigate the problem of 3D object categorization of objects typically present in kitchen environments, from data acquired using a composite sensor. Our fra...
Zoltan Csaba Marton, Radu Bogdan Rusu, Dominik Jai...
NIPS
2008
15 years 7 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
CVPR
2003
IEEE
16 years 8 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
UM
2005
Springer
15 years 12 months ago
Bayesphone: Precomputation of Context-Sensitive Policies for Inquiry and Action in Mobile Devices
Inference and decision making with probabilistic user models may be infeasible on portable devices such as cell phones. We highlight the opportunity for storing and using precomput...
Eric Horvitz, Paul Koch, Raman Sarin, Johnson Apac...
KCAP
2009
ACM
16 years 27 days ago
POIROT: acquiring workflows by combining models learned from interpreted traces
The POIROT project is a four-year effort to develop an architecture that integrates the products of a number of targeted reasoning and learning components to produce executable re...
Mark H. Burstein, Fusun Yaman, Robert Laddaga, Rob...