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» Learning By Observation Using Qualitative Spatial Relations
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CVPR
2007
IEEE
14 years 9 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
TSP
2010
13 years 2 months ago
Testing stationarity with surrogates: a time-frequency approach
An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a ...
Pierre Borgnat, Patrick Flandrin, Paul Honeine, C&...
ICRA
2007
IEEE
128views Robotics» more  ICRA 2007»
14 years 2 months ago
Autonomous Robotic Sensing Experiments at San Joaquin River
Abstract— Distributed, high-density spatiotemporal observations are proposed for answering many river-related questions, including those pertaining to hydraulics and multi-dimens...
Amarjeet Singh 0003, Maxim A. Batalin, Victor Chen...
ICMLA
2007
13 years 9 months ago
Estimating class probabilities in random forests
For both single probability estimation trees (PETs) and ensembles of such trees, commonly employed class probability estimates correct the observed relative class frequencies in e...
Henrik Boström
BMVC
2010
13 years 5 months ago
Manifold Learning for ToF-based Human Body Tracking and Activity Recognition
In this paper, we propose a method for simultaneous human full-body pose tracking and activity recognition from time-of-flight (ToF) camera images. Simple and sparse depth cues ar...
Loren Arthur Schwarz, Diana Mateus, Victor Castane...